Structured Query Language (SQL) is the de facto query language for most relational databases, containing commands used to access and manipulate data. Since released by 146, SQL has been used by most database vendors for their products. Although SQL is highly declarative, many end-users encounter several challenges in writing correct queries. Such challenges have limited its use as the preferred database language of choice. This part of the thesis provides an introduction to what SQL is, describes several terms used, and reviews literature similar to this work.

This part contains three chapters. <ref> introduces and provides the context for this
research. <ref> outlines several definitions that were used in this study. <ref> presents the literature on SQL comprehension and other areas of study.

Introduction and Background

Teaching queries in plain English eliminating syntactic barriers, is the goal of achieving SQL comprehension. This approach to teaching was first proposed by 227 and regarded as the SFA. To aid program comprehension, this approach to teaching was termed narrations by 8. This approach helps to abstract a program without first considering the syntax of the language. Since SQL have less control structures, we have extended this approach of teaching for SQL for the first time, ignoring the syntax that describes unique sets of rules and guidelines of the language. The technique described was used for the automatic generation of explanations for simple queries using REs. In addition, to aid the understanding of nested queries, a CFG was used to recognise nested queries in an attempt to improve comprehension for these types of queries.

This part comprises of two chapters. <ref> presents a formal technique, using REs to recognise simple SQL queries and describes the tool designed. In <ref>, a CFG was described for the recognition of nested queries and a tool was designed for the automatic generation of narrations for nested queries.

SQL Comprehension and Narration

Automatic synthesis of problems into SQL is instrumental to end-users with diverse backgrounds such as business analysts, financial professionals, marketing personnel, etc [710, 740]. These users frequently use db applications but lack the technical expertise to write a correct SQL query. Although these users can clearly describe what tasks they intend to perform, they are often faced with how to specify what the intended query should be. Such confusion may increase if they frequently need to engage with technical staff or seek help through online forums just to perform their daily operation. Such process can be time-consuming and frustrating. To mitigate these challenges, we propose different interactive user interfaces that these users can engage with. First, we present a tool that allows a user to specify their query requests in a free-form termed as narrations, then we show an interactive visualiser that uses drag and drop interactions to generate a query using icons. Last, we present a speech-query tool that takes a speech input and converts this into a query output.

This part contains three chapters. In <ref>, we describe the translation of narrations into SQL queries and in <ref>, the visualiser for SQL queries is presented. <ref> describes the speech synthesiser tool for SQL queries.

SQL Synthesis

Throughout this study, we have presented a number of algorithms together with some software prototypes that assist end-users comprehend SQL queries. These prototypes are (i) , a narrator for explaining SQL queries using predefined templates; (ii) , an improved SQL narrator for nested queries; (iii) , a tool that translates a narration into SQL queries; (iv) , a visualisation tool that uses the drag and drop interaction for query generation; and (v) , a speech-based query tool, that converts speech into SQL queries. For each prototype, we examine end-users' perceptions and form a basis for future studies. Many evaluations were conducted using an online means, and where necessary, we undertook some performance evaluation.

This part consists of two chapters. In <ref>, we present the evaluation results for the prototypes designed in this study and provide the conclusion with discussions for future work in <ref>.

Evaluations, Conclusions and Future Work

[1]
Daniel Abadi, Peter Boncz, Stavros Harizopoulos, Stratos Idreos, Samuel Madden,
et al.
The design and implementation of modern column-oriented database
Foundations and Trends® in Databases,
5(3):197–280, 2013.

[2]
Alberto Abelló, M Elena Rodríguez, Toni Urpí, Xavier Burgués,
M José Casany, Carme Martín, and Carme Quer.
LEARN-SQL: Automatic assessment of SQL based on IMS QTI
In Eighth IEEE International Conference on Advanced Learning
Technologies, pages 592–593. IEEE, 2008.

[3]
Serge Abiteboul, Rakesh Agrawal, Phil Bernstein, Mike Carey, Stefano Ceri,
Bruce Croft, David DeWitt, Mike Franklin, Hector Garcia Molina, Dieter
Gawlick, et al.
The Lowell database research self-assessment.
Communications of the ACM, 48(5):111–118, 2005.

[4]
Nancy E Adams.
Bloom’s taxonomy of cognitive learning objectives.
Journal of the Medical Library Association: JMLA, 103(3):152,

[5]
Marilyn Jager Adams.
Failures to comprehend and levels of processing.
Theoretical issues in reading comprehension: Perspectives from
cognitive psychology, linguistics, artificial intelligence and education,
11:11, 2017.

[6]
Abejide Ade-Ibijola and George Obaido.
S-NAR: generating narrations of SQL queries using regular
In the ACM proceedings of Proceedings of the South African
Institute of Computer Scientists and Information Technologists, pages
11–18, 2017.
Bloemfontein, Free State. ISBN: 978-1-4503-5250-5.
<https://dl.acm.org/citation.cfm?doid=3129416.3129454>. [South Africa].

[7]
Abejide Ade-Ibijola and George Obaido.
XNorthwind: Grammar-driven synthesis of large datasets for DB
In In International Journal of Computer Science (Scopus), pages
541–551, 2019.
International Association of Engineers (IAENG).
<http://www.iaeng.org/IJCS/issues_v46/issue_4/IJCS_46_4_05.pdf>. [Hong

[8]
Abejide Ade-Ibijola, Sigrid Ewert, and Ian Sanders.
Abstracting and narrating novice programs using regular expressions.
In Proceedings of the Annual Conference of the South African
Institute of Computer Scientists and Information Technologists (SAICSIT),
Centurion, pages 19–28, 2014.
ACM International Conference Series, doi: 10.1145/2664591.2664601,
<http://dl.acm.org/citation.cfm?id=2664601> [South Africa].

[9]
Abejide Ade-Ibijola, Sigrid Ewert, and Ian Sanders.
Introducing Code Adviser: A DFA-driven electronic programming
In Implementation and Application of Automata, Umeå,, pages
307–312, 2015.
Springer LNCS 9223, doi: 10.1007/978-3-319-22360-525,
<http://link.springer.com/chapter/10.1007/978-3-319-22360-5_25> [Sweden].

[10]
Abejide Ade-Ibijola.
FINCHAN: A grammar-based tool for automatic comprehension of
financial instant messages.
In Proceedings of the Annual Conference of the South African
Institute of Computer Scientists and Information Technologists (SAICSIT),
pages 1–10, 2016.
Johannesburg. ACM International Conference Series, ISBN:
978-1-4503-4805-8, <http://dl.acm.org/citation.cfm?id=2987518>, doi:
<http://dx.doi.org/10.1145/2987491.2987518> [South Africa].

[11]
Abejide Olu Ade-Ibijola.
Automatic novice program comprehension for semantic bug
detection, 2016.
A research thesis submitted for the award of Doctor of Philosophy in
Computer Science, WITS [South Africa]. Available online:

[12]
Abejide Ade-Ibijola.
Automata-aided estimation of similarity in novice programs.
In the proceedings of 46th Annual South African Computer
Lecturers' Association (SACLA),, pages 23–38, 2017.
Magaliesburg, North-west, ISBN: 978-1-86822-846-1.
<http://hdl.handle.net/10210/241253> [South Africa].

[13]
Abejide Ade-Ibijola.
New finite automata applications in novice program
ISBN: 978-3-330-02905-7, LAP Lambert Academic Publishing,
Bahnhofstrasse 28, Saarbrücken, URL:

[14]
Abejide Ade-Ibijola.
Synthesis of social media profiles using a probabilistic context-free
In the proceedings of the IEEE Conference of the Pattern
Recognition Association of South Africa, Robotics, and Mechatronics
(PRASA-RobMech), pages 104–109, 2017.
Bloemfontein. ISBN: 978-1-5386-2313-8/17.
<http://ieeexplore.ieee.org/document/8261131/> [South Africa].

[15]
Abejide Ade-Ibijola.
Syntactic generation of practice novice programs in Python.
In Communications in Computer and Information Science (CCIS),
volume 963, pages 158–172, 2018.
Springer, Cham (Scopus). ISBN: 978-3-030-05813-5.

[16]
Abejide Ade-Ibijola.
Synthesis of regular expression problems and solutions.
In International Journal of Computers and Applications (Scopus),
Taylor’s and Francis., pages 1–17, 2018.
URL: <www.tandfonline.com/doi/full/10.1080/1206212X.2018.1482398>
[United Kingdom].

[17]
Abejide Ade-Ibijola.
Synthesis of hypothetical sociograms for social network analysis.
In 5th IEEE International Conference on Soft Computing &
Machine Intelligence (ISCMI), Nairobi, pages 79–83, 2019.
URL: <https://ieeexplore.ieee.org/document/8703221>. [Kenya].

[18]
Katrin Affolter, Kurt Stockinger, and Abraham Bernstein.
A comparative survey of recent natural language interfaces for
arXiv preprint arXiv:1906.08990, 2019.

[19]
Deepak Kumar Agarwal and Rahul Kumar.
Spam filtering using SVM with different kernel functions.
International Journal of Computer Applications,
136(5):0975–8887, 2016.

[20]
Alireza Ahadi, Julia Prior, Vahid Behbood, and Raymond Lister.
A quantitative study of the relative difficulty for novices of
writing seven different types of SQL queries.
In Proceedings of the ACM Conference on Innovation and
Technology in Computer Science Education, pages 201–206. ACM, 2015.

[21]
Alireza Ahadi, Vahid Behbood, Arto Vihavainen, Julia Prior, and Raymond Lister.
Students' syntactic mistakes in writing seven different types of
SQL queries and its application to predicting students' success.
In Proceedings of the 47th ACM Technical Symposium on Computing
Science Education, pages 401–406. ACM, 2016.

[22]
Alfred V Aho, Ravi Sethi, and Jeffrey D Ullman.
Compilers, principles, techniques.
Addison Wesley, 7(8):9, 1986.

[23]
Andrew Aken and Michael D Michalisin.
The impact of the skills gap on the recruitment of MIS graduates.
In Proceedings of the 2007 ACM SIGMIS CPR conference on Computer
personnel research: The global information technology workforce, pages
105–111. ACM, 2007.

[24]
Fouad Nasser A Al Omran and Christoph Treude.
Choosing an NLP library for analyzing software documentation: a
systematic literature review and a series of experiments.
In Proceedings of the 14th International Conference on Mining
Software Repositories, pages 187–197. IEEE Press, 2017.

[25]
Qasem A Al-Radaideh and Mohammed A Al-Abrat.
An Arabic text categorization approach using term weighting and
multiple reducts.
Soft Computing, 23(14):5849–5863, 2019.

[26]
Huda Al-Shuaily and Karen Renaud.
SQL patterns-a new approach for teaching SQL.
In 8th HEA Workshop on Teaching, Learning and Assessment of
Databases, Abertay-Dundee, pages 29–40, 2010.

[27]
Huda Al Shuaily and Karen Renaud.
A framework for SQL learning: Linking learning taxonomy, cognitive
model and cross cutting factors.
World Academy of Science, Engineering and Technology,
International Journal of Social, Behavioral, Educational, Economic, Business
and Industrial Engineering, 10(9):3091–3097, 2016.

[28]
Huda Al Shuaily and Karen Renaud.
A model of SQL learning.

[29]
Huda Al-Shuaily.
SQL pattern design, development & evaluation of its
PhD thesis, University of Glasgow, 2013.

[30]
Rami Aldahdooh and Samy S Abu Naser.
Development and evaluation of the Oracle Intelligent Tutoring

[31]
Christopher Alexander.
A pattern language: towns, buildings, construction.
Oxford university press, 1977.

[32]
Brett Allenstein, Andrew Yost, Paul Wagner, and Joline Morrison.
A query simulation system to illustrate database query execution.
ACM Special Interest Group on Computer Science Education
Bulletin, 40(1):493–497, 2008.

[33]
Bander Alsajjan and Charles Dennis.
Internet banking acceptance model: Cross-market examination.
Journal of Business Research, 63(9):957–963, 2010.

[34]
Nabeel T Alsohybe, Neama Abdulaziz Dahan, and Fadl Mutaher Ba-Alwi.
Machine-translation history and evolution: Survey for
Arabic-English translations.
arXiv preprint arXiv:1709.04685, 2017.

[35]
Dario Amodei, Sundaram Ananthanarayanan, Rishita Anubhai, Jingliang Bai, Eric
Battenberg, Carl Case, Jared Casper, Bryan Catanzaro, Qiang Cheng, Guoliang
Chen, et al.
Deep speech 2: End-to-end speech recognition in English and
In International conference on machine learning, pages
173–182, 2016.

[36]
Ol'ga Vyacheslavovna Andreeva, Mirabbas Bakhtiyarovich Bagirov,
Anastasiya Aleksandrovna Dankina, Tat'yana Olegovna Fedorova, and
Mariya Mikhailovna Sheveleva.
Intellectual analysis of data on the basis of Stanford coreNLP
for PoS tagging of texts in the Russian language.
Sistemy i Sredstva Informatiki [Systems and Means of
Informatics], 28(2):145–153, 2018.

[37]
Gabor Angeli, Sonal Gupta, Melvin Johnson Premkumar, Christopher D Manning,
Christopher Ré, Julie Tibshirani, Jean Y Wu, Sen Wu, and Ce Zhang.
Stanford’s distantly supervised slot filling systems for kbp 2014.
In Proceedings of the Seventh Text Analysis Conference, 2014.

[38]
Arvind Arasu, Brian Babcock, Shivnath Babu, John Cieslewicz, Mayur Datar, Keith
Ito, Rajeev Motwani, Utkarsh Srivastava, and Jennifer Widom.
Stream: The Stanford Data Stream Management System.
In Data Stream Management, pages 317–336. Springer, 2016.

[39]
Carmelo Ardito, Maria Francesca Costabile, and Hans-Christian Jetter.
Gestures that people can understand and use.
Journal of Visual Languages & Computing, 25(5):572–576, 2014.

[40]
Michael Armbrust, Reynold S Xin, Cheng Lian, Yin Huai, Davies Liu, Joseph K
Bradley, Xiangrui Meng, Tomer Kaftan, Michael J Franklin, Ali Ghodsi, et al.
Spark SQL: Relational data processing in spark.
In Proceedings of the 2015 ACM SIGMOD International Conference
on Management of Data, pages 1383–1394. ACM, 2015.

[41]
Mikel Artetxe, Gorka Labaka, Eneko Agirre, and Kyunghyun Cho.
Unsupervised neural machine translation.
arXiv preprint arXiv:1710.11041, 2017.

[42]
Kanokwan Atchariyachanvanich, Srinual Nalintippayawong, and Tanasab Permpool.
Development of a mySQL sandbox for processing SQL statements:
Case of DML and DDL statements.
In 2017 14th International Joint Conference on Computer Science
and Software Engineering (JCSSE), pages 1–6. IEEE, 2017.

[43]
Sofia J Athenikos and Hyoil Han.
Biomedical question answering: A survey.
Computer methods and programs in biomedicine, 99(1):1–24,

[44]
Laura Auria and Rouslan A Moro.
Support vector machines (SVM) as a technique for solvency analysis.

[45]
Mariette Awad and Rahul Khanna.
Efficient learning machines: theories, concepts, and
applications for engineers and system designers.
Apress, 2015.

[46]
Samy A Azer, Michelle Mclean, Hirotaka Onishi, Masami Tagawa, and Albert
Cracks in problem-based learning: What is your action plan?
Medical teacher, 35(10):806–814, 2013.

[47]
Dzmitry Bahdanau, Kyunghyun Cho, and Yoshua Bengio.
Neural machine translation by jointly learning to align and
arXiv preprint arXiv:1409.0473, 2014.

[48]
Dzmitry Bahdanau, Jan Chorowski, Dmitriy Serdyuk, Philemon Brakel, and Yoshua
End-to-end attention-based large vocabulary speech recognition.
In 2016 IEEE international conference on acoustics, speech and
signal processing (ICASSP), pages 4945–4949. IEEE, 2016.

[49]
Christopher Baik, HV Jagadish, and Yunyao Li.
Bridging the semantic gap with SQL query logs in natural language
interfaces to databases.
In 2019 IEEE 35th International Conference on Data Engineering
(ICDE), pages 374–385. IEEE, 2019.

[50]
Jason Baldridge.
The openNLP project.
URL: http://opennlp. apache. org/index. html,(accessed 2
February 2012), page 1, 2005.

[51]
Mark H Barber, Carsten Hagemann, and Christopher J Hockings.
Similar email spam detection, 2018.
US Patent App. 15/270,237.

[52]
Jorge Barrera and George Pachitariu.
Big data: What is it? and is my data big enough?

[53]
Andrew B Barron, Eileen A Hebets, Thomas A Cleland, Courtney L Fitzpatrick,
Mark E Hauber, and Jeffrey R Stevens.
Embracing multiple definitions of learning.
Trends in neurosciences, 38(7):405–407, 2015.

[54]
Hannah Bast and Elmar Haussmann.
More accurate question answering on freebase.
In Proceedings of the 24th ACM International on Conference on
Information and Knowledge Management, pages 1431–1440. ACM, 2015.

[55]
Osbert Bastani, Rahul Sharma, Alex Aiken, and Percy Liang.
Synthesizing program input grammars.
In ACM Special Interest Group on Programming Languages,
volume 52, pages 95–110. ACM, 2017.

[56]
John Bateman and Michael Zock.
Natural language generation.
In The Oxford Handbook of Computational Linguistics 2nd
edition. 2003.

[57]
Madeleine Bates.
Models of natural language understanding.
Proceedings of the National Academy of Sciences,
92(22):9977–9982, 1995.

[58]
Carlo Batini, Tiziana Catarci, Maria Francesca Costabile, and Stefano Levialdi.
Visual query systems: A taxonomy.
In VDB, pages 153–168, 1991.

[59]
Rahul Batra.
A history of SQL and relational databases.
In SQL Primer, pages 183–187. Springer, 2018.

[60]
David Bau.
Droplet, a blocks-based editor for text code.
Journal of Computing Sciences in Colleges, 30(6):138–144,

[61]
Adil Baykasoğlu, Burcu K Özbel, Nurhan Dudaklı, Kemal Subulan, and
Mümin Emre Şenol.
Process mining based approach to performance evaluation in
computer-aided examinations.
Computer Applications in Engineering Education,
26(5):1841–1861, 2018.

[62]
Alan Beaulieu.
Learning SQL: Master SQL Fundamentals.
" O'Reilly Media, Inc.", 2009.

[63]
Suren Behari, Aileen Cater-Steel, and Jeffrey Soar.
Data science and big data analytics in financial services: A case
Handbook of Research on Driving Competitive Advantage through
Sustainable, Lean, and Disruptive Innovation, page 396, 2016.

[64]
Yonatan Belinkov, Mitra Mohtarami, Scott Cyphers, and James Glass.
Vectorslu: A continuous word vector approach to answer selection in
community question answering systems.
In Proceedings of the 9th International Workshop on Semantic
Evaluation (SemEval 2015), pages 282–287, 2015.

[65]
Asa Ben-Hur and Jason Weston.
A user’s guide to support vector machines.
In Data mining techniques for the life sciences, pages
223–239. Springer, 2010.

[66]
Yoshua Bengio and Jean-Sébastien Senécal.
Adaptive importance sampling to accelerate training of a neural
probabilistic language model.
IEEE Transactions on Neural Networks, 19(4):713–722, 2008.

[67]
Yoshua Bengio, Réjean Ducharme, Pascal Vincent, and Christian Jauvin.
A neural probabilistic language model.
Journal of machine learning research, 3(Feb):1137–1155, 2003.

[68]
Jon Bentley.
Programming Pearls.
Addison–Wesley, Boston, MA, USA, 2nd edition, 1999.

[69]
Jonathan Berant and Percy Liang.
Semantic parsing via paraphrasing.
In Proceedings of the 52nd Annual Meeting of the Association for
Computational Linguistics (Volume 1: Long Papers), pages 1415–1425, 2014.

[70]
Joseph Bergin, Jutta Eckstein, M Manns, H Sharp, K Marquardt, Jane Chandler,
M Sipos, M Volter, and E Wallingford.
Pedagogical patterns: advice for educators.
CreateSpace, 2012.

[71]
Dave Berque, Terri Bonebright, Seth Kinnett, Nathan Nichols, and Adam Peters.
A case study in the design of software that uses auditory cues to
help low vision students view notes on a blackboard.
Georgia Institute of Technology, 2003.

[72]
Kirsten Berthold, Tessa HS Eysink, and Alexander Renkl.
Assisting self-explanation prompts are more effective than open
prompts when learning with multiple representations.
Instructional Science, 37(4):345–363, 2009.

[73]
Jiang Bian, Bin Gao, and Tie-Yan Liu.
Knowledge-powered deep learning for word embedding.
In Joint European conference on machine learning and knowledge
discovery in databases, pages 132–148. Springer, 2014.

[74]
Ilia Bider and David Rogers.
YASQLT–Yet Another SQL Tutor.
In International Conference on Conceptual Modeling, pages
197–206. Springer, 2016.

[75]
Metin Bilgin.
A study on named entity recognition with openNLP at English
Journal of Applied Intelligent System, 4(1):1–8, 2019.

[76]
Steven Bird, Ewan Klein, Edward Loper, and Jason Baldridge.
Multidisciplinary instruction with the natural language toolkit.
In Proceedings of the Third Workshop on Issues in Teaching
Computational Linguistics, pages 62–70. Association for Computational
Linguistics, 2008.

[77]
Steven Bird, Ewan Klein, and Edward Loper.
Natural language processing with Python: analyzing text with
the natural language toolkit.
" O'Reilly Media, Inc.", 2009.

[78]
Steven Bird.
Computational phonology.
arXiv preprint cs/0204023, 2002.

[79]
Daniel G Bobrow, Ronald M Kaplan, Martin Kay, Donald A Norman, Henry Thompson,
and Terry Winograd.
Gus, a frame-driven dialog system.
Artificial intelligence, 8(2):155–173, 1977.

[80]
Tom Bocklisch, Joey Faulkner, Nick Pawlowski, and Alan Nichol.
Rasa: Open source language understanding and dialogue management.
arXiv preprint arXiv:1712.05181, 2017.

[81]
Travis A Bogard.
Instant messaging via telephone interfaces.
Google Patents, 2004.

[82]
Alessandro Bondielli, Lucia C Passaro, and Alessandro Lenci.
CoreNLP-it: A UD pipeline for italian based on Stanford
In CLiC-it, 2018.

[83]
Graeme F Bonham-Carter.
Geographic information systems for geoscientists: modelling with
GIS, volume 13.
Elsevier, 2014.

[84]
Jan O Borchers and John C Thomas.
Patterns: what's in it for HCI?
In CHI'01 extended abstracts on Human factors in computing
systems, pages 225–226. ACM, 2001.

[85]
Jan O Borchers.
Interaction design patterns: twelve theses.
In Workshop, The Hague, volume 2, page 3. Citeseer, 2000.

[86]
Richard Bornat.
Programming from First Principles.
Prentice Hall International (UK) Ltd., Hertfordshire, UK, UK, 1987.

[87]
Andrey Borodin, Yuri Kiselev, Sergey Mirvoda, and Sergey Porshnev.
Development of data aggregation capabilities in domain-specific query
language for metallurgy.
In 2016 Dynamics of Systems, Mechanisms and Machines
(Dynamics), pages 1–6. IEEE, 2016.

[88]
Maura Borrego.
Development of engineering education as a rigorous discipline: A
study of the publication patterns of four coalitions.
Journal of Engineering Education, 96(1):5–18, 2007.

[89]
Bernhard E Boser, Isabelle M Guyon, and Vladimir N Vapnik.
A training algorithm for optimal margin classifiers.
In Proceedings of the 5th Annual ACM Workshop on Computational
Learning Theory, pages 144–152, 2003.

[90]
Kevin K Bowden, Shereen Oraby, Amita Misra, Jiaqi Wu, Stephanie Lukin, and
Marilyn Walker.
Data-driven dialogue systems for social agents.
In Advanced Social Interaction with Agents, pages 53–56.
Springer, 2019.

[91]
Matt Bower.
A taxonomy of task types in computing.
In ACM SIGCSE Bulletin, volume 40, pages 281–285. ACM, 2008.

[92]
Laura Bozzelli, Bastien Maubert, and Sophie Pinchinat.
Uniform strategies, rational relations and jumping automata.
Information and Computation, 242:80–107, 2015.

[93]
Robert Bringhurst.
The Elements of Typographic Style.
Version 4.0: 20th Anniversary Edition. Hartley & Marks Publishers,
Point Roberts, WA, USA, 2013.

[94]
Roderic Broadhurst and Harshit Trivedi.
Malware in spam email: Trends in the 2016 australian spam
intelligence data.
Available at SSRN 3413442, 2018.

[95]
Karin Brodie.
Learning about learner errors in professional learning communities.
Educational Studies in Mathematics, 85(2):221–239, 2014.

[96]
Ruven Brooks.
Towards a theory of the cognitive processes in computer programming.
International Journal of Man-Machine Studies, 9(6):737–751,

[97]
C Marlin Brown.
Human-computer interface design guidelines.
Intellect Books, 1998.

[98]
Anne Brüggemann-Klein and Derick Wood.
One-unambiguous regular languages.
Information and Computation, 142(2):182–206, 1998.

[99]
Jerome Seymour Bruner et al.
Toward a theory of instruction, volume 59.
Harvard University Press, 1966.

[100]
Peter Brusilovsky, Sergey Sosnovsky, Danielle H Lee, Michael Yudelson, Vladimir
Zadorozhny, and Xin Zhou.
An open integrated exploratorium for database courses.
In ACM Special Interest Group on Computer Science Education
Bulletin, volume 40, pages 22–26. ACM, 2008.

[101]
Duy Duc An Bui and Qing Zeng-Treitler.
Learning regular expressions for clinical text classification.
Journal of the American Medical Informatics Association,
21(5):850–857, 2014.

[102]
Dragos Burileanu.
Spoken language interfaces for embedded applications.
In Human factors and voice interactive systems, pages 135–161.
Springer, 2008.

[103]
Mikhail Burtsev, Alexander Seliverstov, Rafael Airapetyan, Mikhail Arkhipov,
Dilyara Baymurzina, Nickolay Bushkov, Olga Gureenkova, Taras Khakhulin, Yuri
Kuratov, Denis Kuznetsov, et al.
Deeppavlov: open-source library for dialogue systems.
In Proceedings of ACL 2018, System Demonstrations, pages
122–127, 2018.

[104]
Luca Cagliero, Luigi De Russis, Laura Farinetti, and Teodoro Montanaro.
Improving the effectiveness of SQL learning practice: a data-driven
In 2018 IEEE 42nd Annual Computer Software and Applications
Conference (COMPSAC), volume 1, pages 980–989. IEEE, 2018.

[105]
Ruichu Cai, Boyan Xu, Xiaoyan Yang, Zhenjie Zhang, Zijian Li, and Zhihao Liang.
An encoder-decoder framework translating natural language to database
arXiv preprint arXiv:1711.06061, 2017.

[106]
Carlos Pampulim Caldeira.
Teaching SQL: a case study.
In ACM Special Interest Group on Computer Science Education
Bulletin, volume 40, pages 340–340. ACM, 2008.

[107]
Erik Cambria and Bebo White.
Jumping NLP curves: A review of natural language processing
IEEE Computational intelligence magazine, 9(2):48–57, 2014.

[108]
Erik Cambria.
Affective computing and sentiment analysis.
IEEE Intelligent Systems, 31(2):102–107, 2016.

[109]
Cezar Câmpeanu, Kai Salomaa, and Sheng Yu.
A formal study of practical regular expressions.
International Journal of Foundations of Computer Science,
14(06):1007–1018, 2003.

[110]
Ivan Cantador, Peter L Brusilovsky, and Tsvi Kuflik.
Second workshop on information heterogeneity and fusion in
recommender systems (hetrec2011).

[111]
James J Cappel.
Entry-level is job skills: A survey of employers.
Journal of Computer Information Systems, 42(2):76–82, 2002.

[112]
Bram CM Cappers and Jarke J van Wijk.
Exploring multivariate event sequences using rules, aggregations, and
IEEE transactions on visualization and computer graphics,
24(1):532–541, 2017.

[113]
Simon Cassidy.
Learning styles: An overview of theories, models, and measures.
Educational psychology, 24(4):419–444, 2004.

[114]
Tiziana Catarci, Maria F Costabile, Stefano Levialdi, and Carlo Batini.
Visual query systems for databases: A survey.
Journal of Visual Languages & Computing, 8(2):215–260, 1997.

[115]
Ariel Gregorio Ceballos, Michael Anthony Caruso, and Kenneth Klaus.
Criteria builder for query builder, November 13 2012.
US Patent 8,312,038.

[116]
Miguel Cebollero, Jay Natarajan, and Michael Coles.
Error handling and dynamic SQL.
In Pro T-SQL Programmer's Guide, pages 589–612. Springer,

[117]
Casey G Cegielski and L Allison Jones-Farmer.
Knowledge, skills, and abilities for entry-level business analytics
positions: A multi-method study.
Decision Sciences Journal of Innovative Education,
14(1):91–118, 2016.

[118]
Maurizio Cembalo, Alfredo De Santis, and Umberto Ferraro Petrillo.
SAVI: a new system for advanced SQL visualization.
In Proceedings of the 2011 conference on Information technology
education, pages 165–170. ACM, 2011.

[119]
Paulo Roberto Massa Cereda and João José Neto.
Instrumenting a context-free language recognizer.
In International Conference on Enterprise Information Systems,
pages 203–210, 2017.

[120]
Seth Chaiklin.
The zone of proximal development in Vygotsky’s analysis of
learning and instruction.
Vygotsky’s educational theory in cultural context, 1:39–64,

[121]
Soumen Chakrabarti.
Breaking through the syntax barrier: Searching with entities and
In European Conference on Machine Learning, pages 9–16.
Springer, 2004.

[122]
Donald D Chamberlin.
Early history of SQL.
IEEE Annals of the History of Computing, 34(4):78–82, 2012.

[123]
Dharmil Chandarana, Vraj Shah, Arun Kumar, and Lawrence Saul.
SpeakQL: towards speech-driven multi-modal querying.
In Proceedings of the 2nd Workshop on Human-In-the-Loop Data
Analytics, page 11. ACM, 2017.

[124]
Ashish Chandra and Mohammad Suaib.
A survey on web spam and spam 2.0.
International Journal of Advanced Computer Research, 4(2):634,

[125]
Po-Yao Chao.
Exploring students' computational practice, design and performance of
problem-solving through a visual programming environment.
Computers & Education, 95:202–215, 2016.

[126]
Iti Chaturvedi, Erik Cambria, Roy E Welsch, and Francisco Herrera.
Distinguishing between facts and opinions for sentiment analysis:
Survey and challenges.
Information Fusion, 44:65–77, 2018.

[127]
Yu-Ren Chen and Hsin-Hsi Chen.
Opinion spam detection in web forum: a real case study.
In Proceedings of the 24th International Conference on World
Wide Web, pages 173–183. International World Wide Web Conferences Steering
Committee, 2015.

[128]
Xingliang Chen, Antonija Mitrovic, and Moffat Mathews.
How much learning support should be provided to novices and advanced
In IEEE 17th International Conference on Advanced Learning
Technologies, pages 39–43. IEEE, 2017.

[129]
Yun-Nung Chen, Asli Celikyilmaz, and Dilek Hakkani-Tür.
Deep learning for dialogue systems.
In Proceedings of ACL 2017, Tutorial Abstracts, pages 8–14,

[130]
Chris Cherpas.
Natural language processing, pragmatics, and verbal behavior.
The Analysis of verbal behavior, 10(1):135–147, 1992.

[131]
Alvin Cheung, Armando Solar-Lezama, et al.
Computer-assisted query formulation.
Foundations and Trends® in Programming
Languages, 3(1):1–94, 2016.

[132]
Roger HL Chiang, Paulo Goes, and Edward A Stohr.
Business intelligence and analytics education, and program
development: A unique opportunity for the information systems discipline.
ACM Transactions on Management Information Systems (TMIS),
3(3):12, 2012.

[133]
Travers Ching, Daniel S Himmelstein, Brett K Beaulieu-Jones, Alexandr A
Kalinin, Brian T Do, Gregory P Way, Enrico Ferrero, Paul-Michael Agapow,
Michael Zietz, Michael M Hoffman, et al.
Opportunities and obstacles for deep learning in biology and
Journal of The Royal Society Interface, 15(141):20170387, 2018.

[134]
Noam Chomsky and David W Lightfoot.
Syntactic structures.
Walter de Gruyter, 2002.

[135]
Noam Chomsky.
Three models for the description of language.
IRE Transactions on information theory, 2(3):113–124, 1956.

[136]
Noam Chomsky.
On certain formal properties of grammars.
Information and control, 2(2):137–167, 1959.

[137]
Frederic T Chong, Diana Franklin, and Margaret Martonosi.
Programming languages and compiler design for realistic quantum
Nature, 549(7671):180, 2017.

[138]
David C Chou and Amy Y Chou.
A guide to the Internet revolution in banking.
Information Systems Management, 17(2):51–57, 2000.

[139]
Gobinda G Chowdhury.
Natural language processing.
Annual review of information science and technology,
37(1):51–89, 2003.

[140]
V Christina, S Karpagavalli, and G Suganya.
A study on email spam filtering techniques.
International Journal of Computer Applications, 12(1):7–9,

[141]
Shumo Chu, Chenglong Wang, Konstantin Weitz, and Alvin Cheung.
Cosette: An automated prover for SQL.
In Conference on Innovative Data Systems Research, 2017.

[142]
Karen Church and Rodrigo de Oliveira.
What's up with Whatsapp?: comparing mobile instant messaging
behaviors with traditional SMS.
In Proceedings of the 15th International Conference on
Human-computer Interaction with Mobile Devices and Services, pages 352–361.
ACM, 2013.

[143]
Andrew Churches.
Bloom's digital taxonomy, 2010.

[144]
Ludec Cienciala, Lucie Ciencialová, and Erzsébet Csuhaj Varjú.
Towards p colonies processing strings.
Proceedings of the Twelfth Brainstorming Week on Membrane
Computing, 103-118, Sevilla, ETS de Ingeniería Informática, 3-7 de
Febrero, 2014,, 2014.

[145]
Jean-Pierre Clayer, Claudine Toffolon, and Christophe Choquet.
Patterns, pedagogical design schemes and process for instructional
In 2013 IEEE 13th International Conference on Advanced Learning
Technologies, pages 304–306. IEEE, 2013.

[146]
Edgar F Codd.
A relational model of data for large shared data banks.
Communications of the ACM, 13(6):377–387, 1970.

[147]
Edgar F Codd.
Seven steps to rendezvous with the casual user.
IBM Corporation, 1974.

[148]
Thomas S Coe.
Using the Bloomberg professional system for finance classes.
Journal of Financial Education, pages 48–62, 2007.

[149]
Kenneth Mark Colby, Sylvia Weber, and Franklin Dennis Hilf.
Artificial paranoia.
Artificial Intelligence, 2(1):1–25, 1971.

[150]
Kenneth Mark Colby.
Artificial paranoia: a computer simulation of paranoid process.
Pergamon Press, 1975.

[151]
Peter Collin.
Dictionary of banking and finance.
Psychology Press, London, 2003.

[152]
Allan Collins and Richard Halverson.
Rethinking education in the age of technology: The digital
revolution and schooling in America.
Teachers College Press, 2018.

[153]
Ronan Collobert and Jason Weston.
A unified architecture for natural language processing: Deep neural
networks with multitask learning.
In Proceedings of the 25th international conference on Machine
learning, pages 160–167. ACM, 2008.

[154]
Ronan Collobert, Jason Weston, Léon Bottou, Michael Karlen, Koray
Kavukcuoglu, and Pavel Kuksa.
Natural language processing (almost) from scratch.
Journal of machine learning research, 12(Aug):2493–2537, 2011.

[155]
Thomas M Connolly and Carolyn E Begg.
Database systems: a practical approach to design,
implementation, and management.
Pearson Education, 2005.

[156]
Thomas M Connolly and Carolyn E Begg.
A constructivist-based approach to teaching database analysis and
Journal of Information Systems Education, 17(1):43, 2006.

[157]
Stanford CoreNLP.
a suite of core NLP tools.
URL http://nlp. stanford. edu/software/corenlp. shtml (Last
accessed: 2019-09-06), page 3, 2016.

[158]
Thomas H. Cormen, Charles E. Leiserson, Ronald L. Rivest, and Clifford Stein.
Introduction to Algorithms.
The MIT Press, Cambridge, MA, USA, 3rd edition, 2009.

[159]
Carlos Coronel and Steven Morris.
Database systems: design, implementation, & management.
Cengage Learning, 2016.

[160]
Cynthia L Corritore and Susan Wiedenbeck.
What do novices learn during program comprehension?
International Journal of Human-Computer Interaction,
3(2):199–222, 1991.

[161]
Marta R Costa-Jussa and José AR Fonollosa.
Character-based neural machine translation.
arXiv preprint arXiv:1603.00810, 2016.

[162]
Benoît Couderc and Jérémy Ferrero.
fr2SQL: Interrogation de bases de données en français.
In 22ème Traitement Automatique des Langues Naturelles,
pages 1–13, 2015.

[163]
Michael A Covington, Barbara J Grosz, and Fernando CN Pereira.
Natural language processing for Prolog programmers.
Prentice hall Englewood Cliffs (NJ), 1994.

[164]
Alison Crowe, Clarissa Dirks, and Mary Pat Wenderoth.
Biology in Bloom: implementing Bloom's taxonomy to enhance
student learning in biology.
CBE—Life Sciences Education, 7(4):368–381, 2008.

[165]
Alan Cruse.
Meaning in language: An introduction to semantics and pragmatics.

[166]
George E Dahl, Dong Yu, Li Deng, and Alex Acero.
Context-dependent pre-trained deep neural networks for
large-vocabulary speech recognition.
IEEE Transactions on audio, speech, and language processing,
20(1):30–42, 2012.

[167]
B. Daigle.
Enterprise to enterprise instant messaging.
Google Patents, US Patent App. 11/300,981, 2007.

[168]
Robert Dale, Hermann Moisl, and Harold Somers.
Handbook of natural language processing.
CRC Press, 2000.

[169]
Robert Dale.
NLP commercialisation in the last 25 years.
Natural Language Engineering, 25(3):419–426, 2019.

[170]
Jonathan Danaparamita and Wolfgang Gatterbauer.
QueryViz: helping users understand SQL queries and their
In Proceedings of the 14th International Conference on Extending
Database Technology, pages 558–561. ACM, 2011.

[171]
Sandipan Dandapat.
Part of specch tagging and chunking with maximum entropy model.
In Proceedings of the IJCAI Workshop on Shallow Parsing for
South Asian Languages, pages 29–32, 2007.

[172]
Wanda P Dann, Stephen Cooper, and Randy Pausch.
Learning to program with Alice.
Prentice Hall Press, 2008.

[173]
Wanda P Dann, Stephen Cooper, and Randy Pausch.
Learning to Program with Alice (w/CD ROM).
Prentice Hall Press, 2011.

[174]
Graham Davey.
Applications of conditioning theory.
Routledge, 2017.

[175]
KH Davis, R Biddulph, and Stephen Balashek.
Automatic recognition of spoken digits.
The Journal of the Acoustical Society of America,
24(6):637–642, 1952.

[176]
Philip Davis.
What computer skills do employees expect from recent college
THE Journal (Technological Horizons in Education), 25(2):74,

[177]
Robert J De Boer and Petra Badke-Schaub.
Interaction between emotions and mental models in engineering and
design activities.
In Emotional Engineering vol. 2, pages 149–164. Springer,

[178]
Jan De Houwer, Dermot Barnes-Holmes, and Agnes Moors.
What is learning? on the nature and merits of a functional definition
of learning.
Psychonomic bulletin & review, 20(4):631–642, 2013.

[179]
Michael De Raadt, Stijn Dekeyser, and Tien Yu Lee.
Do students SQLify? improving learning outcomes with peer review
and enhanced computer assisted assessment of querying skills.
In Proceedings of the 6th Baltic Sea conference on Computing
education research: Koli Calling 2006, pages 101–108. ACM, 2006.

[180]
Michael De Raadt, Stijn Dekeyser, and Tien Yu Lee.
A system employing peer review and enhanced computer assisted
assessment of querying skills.
Informatics in education, 6(1):163, 2007.

[181]
NH Nisansa D de Silva.
Relational databases and biomedical big data.
Bioinformatics in MicroRNA Research, pages 69–81, 2017.

[182]
Andy Dearden and Janet Finlay.
Pattern languages in HCI: A critical review.
Human–computer interaction, 21(1):49–102, 2006.

[183]
Stijn Dekeyser, Michael de Raadt, and Tien Yu Lee.
Computer assisted assessment of SQL query skills.
In Proceedings of the eighteenth conference on Australasian
database-Volume 63, pages 53–62. Australian Computer Society, Inc., 2007.

[184]
Li Deng, Jinyu Li, Jui-Ting Huang, Kaisheng Yao, Dong Yu, Frank Seide, Michael
Seltzer, Geoff Zweig, Xiaodong He, Jason Williams, et al.
Recent advances in deep learning for speech research at microsoft.
In 2013 IEEE International Conference on Acoustics, Speech and
Signal Processing, pages 8604–8608. IEEE, 2013.

[185]
Li Deng, Dong Yu, et al.
Deep learning: methods and applications.
Foundations and Trends® in Signal Processing,
7(3–4):197–387, 2014.

[186]
Luca Di Persio and Oleksandr Honchar.
Artificial neural networks approach to the forecast of stock market
price movements.
International Journal of Economics and Management Systems, 1,

[187]
Suzanne W Dietrich, Eric Eckert, and Kevin Piscator.
WinRDBI: a windows-based relational database educational tool.
In ACM Special Interest Group on Computer Science Education
Bulletin, volume 29, pages 126–130. ACM, 1997.

[188]
Charles J Digate, Christopher F Herot, Tonytip Ketudat, Alexis M Kopikis, and
Daniel J Teven.
System and method for immediate and delayed real-time communication
activities using availability data from communication through an external
instant messaging system.
US Patent 8,375,092, 2013.

[189]
Quan Do, Rajeev K Agrawal, Dhana Rao, and Venkat N Gudivada.
Automatic generation of SQL queries.
American Society for Engineering Education, Paper ID, 8958,

[190]
Robert Dollinger.
SQL lightweight tutoring module–semantic analysis of SQL queries
based on XML representation and LINQ.
In EdMedia: World Conference on Educational Media and
Technology, pages 3323–3328. Association for the Advancement of Computing
in Education, 2010.

[191]
Pál Dömösi, Szilárd Zsolt Fazekas, and Masami Ito.
On Chomsky Hierarchy of Palindromic Languages.
Acta Cybern., 22(3):703–713, 2016.

[192]
Elizabeth J Done and Mike Murphy.
The responsibilisation of teachers: a neoliberal solution to the
problem of inclusion.
Discourse: Studies in the Cultural Politics of Education,
39(1):142–155, 2018.

[193]
Mohnish Dubey, Sourish Dasgupta, Ankit Sharma, Konrad Höffner, and Jens
Asknow: A framework for natural language query formalization in
In European Semantic Web Conference, pages 300–316. Springer,

[194]
Gunter Dueck.
Dueck's Trilogie: Omnisophie – Supramanie –
Springer, Berlin, Germany, 2005.

[195]
Thomas M Duffy and David H Jonassen.
Constructivism and the technology of instruction: A
Routledge, 2013.

[196]
Kevin Duh.
Bayesian Analysis in Natural Language Processing, 2018.

[197]
Susan Dumais, John Platt, David Heckerman, and Mehran Sahami.
Inductive learning algorithms and representations for text

[198]
Andrew Duncan.
Demonstration of Bloomberg terminal and instant Bloomberg
Personal Communication, 2015.

[199]
Rita Stafford Dunn and Kenneth J Dunn.
Teaching students through their individual learning styles: A
practical approach.
Prentice Hall, 1978.

[200]
Maximilian Eberl and Stephan Kaiser.
Organizational Routines Meet Experimental Psycholo: The Role of
Implicit Learning in the Modification of Organizational Routines.
Springer, 2018.

[201]
Amnon H Eden, Epameinondas Gasparis, Jon Nicholson, and Rick Kazman.
Round-trip engineering with the two-tier programming toolkit.
Software Quality Journal, 26(2):249–271, 2018.

[202]
Mohammed A El-Affendi.
The generative power of Arabic morphology and implications: A case
for pattern orientation in Arabic corpus annotation and a proposed pattern
In 5th International Symposium on Data Mining Applications,
pages 36–45. Springer, 2018.

[203]
Marvin Elder.
Natural language database querying, April 30 2009.
US Patent App. 12/004,255.

[204]
Mostafa Elhemali, César A Galindo-Legaria, Torsten Grabs, and Milind M
Execution strategies for SQL subqueries.
In Proceedings of the ACM SIGMOD International Conference on
Management of Data, pages 993–1004. ACM, 2007.

[205]
Geoffrey Ellis and Alan Dix.
A taxonomy of clutter reduction for information visualisation.
IEEE transactions on visualization and computer graphics,
13(6):1216–1223, 2007.

[206]
Geoffrey Ellis and Florian Mansmann.
Mastering the information age solving problems with visual analytics.
In Eurographics, volume 2, page 5, 2010.

[207]
Ramez Elmasri.
Fundamentals of database systems.

[208]
Khaled Nasser ElSayed.
An Arabic natural language interface system for a database of the
Holy Quran.
International Journal of Advanced Research in Artificial
Intelligence, 4(7):9–14, 2015.

[209]
Mark Elsom-Cook.
Intelligent computer-aided instruction research at the open
university. cite report no. 10.

[210]
Yrjö Engeström and Annalisa Sannino.
Whatever happened to process theories of learning?
Learning, Culture and Social Interaction, 1(1):45–56, 2012.

[211]
Noel Entwistle and Paul Ramsden.
Understanding student learning (Routledge revivals).
Routledge, 2015.

[212]
Kent Eriksson, Katri Kerem, and Daniel Nilsson.
Customer acceptance of Internet banking in Estonia.
International Journal of Bank Marketing, 23(2):200–216, 2005.

[213]
Peggy A Ertmer and Timothy J Newby.
Behaviorism, cognitivism, constructivism: Comparing critical features
from an instructional design perspective.
Performance improvement quarterly, 26(2):43–71, 2013.

[214]
Oren Etzioni and Henry Kautz.
High precision natural language interfaces to databases: a graph
theoretic approach draft.

[215]
Theodoros Evgeniou and Massimiliano Pontil.
Workshop on support vector machines: theory and applications.

[216]
AI Explosion.
spaCy-industrial-strength natural language processing in Python.
URL: https://spacy. io, 2017.

[217]
Enaitz Ezpeleta, Urko Zurutuza, and José María Gómez Hidalgo.
Does sentiment analysis help in Bayesian spam filtering?
In International Conference on Hybrid Artificial Intelligence
Systems, pages 79–90. Springer, 2016.

[218]
Ronald Fagin, Benny Kimelfeld, Frederick Reiss, and Stijn Vansummeren.
Document spanners: A formal approach to information extraction.
Journal of the ACM (JACM), 62(2):12, 2015.

[219]
Xiang Fang, Sooun Lee, and Seokha Koh.
Transition of knowledge/skills requirement for entry-level is
professionals: An exploratory study based on recruiters' perception.
Journal of Computer Information Systems, 46(1):58–70, 2005.

[220]
M Amin Farajian, Marco Turchi, Matteo Negri, and Marcello Federico.
Multi-domain neural machine translation through unsupervised
In Proceedings of the Second Conference on Machine Translation,
pages 127–137, 2017.

[221]
Stephane Faroult and Peter Robson.
The art of SQL.
" O'Reilly Media, Inc.", 2006.

[222]
Richard M Felder, Linda K Silverman, et al.
Learning and teaching styles in engineering education.
Engineering education, 78(7):674–681, 1988.

[223]
Patrick Felicia and IJ Pitt.
Profiling users in educational games.
Games-based learning advancement for multisensory human computer
interfaces: Techniques and effective practices, Idea-Group, Hershey, 2009.

[224]
Huan Feng, Kassem Fawaz, and Kang G Shin.
Continuous authentication for voice assistants.
In Proceedings of the 23rd Annual International Conference on
Mobile Computing and Networking, pages 343–355. ACM, 2017.

[225]
Mike Ferguson.
E paper.
BMJ, pages 72–73, 2014.

[226]
Henning Fernau, Meenakshi Paramasivan, and Markus L Schmid.
Jumping finite automata: characterizations and complexity.
In International Conference on Implementation and Application of
Automata, pages 89–101. Springer, 2015.

[227]
Sally Fincher.
What are we doing when we teach programming?
In FIE'99 Frontiers in Education. 29th Annual Frontiers in
Education Conference. Designing the Future of Science and Engineering
Education. Conference Proceedings (IEEE Cat. No. 99CH37011, volume 1, pages
12A4–1. IEEE, 1999.

[228]
Sandra Fleming, Gabrielle Mckee, and Sylvia Huntley-Moore.
Undergraduate nursing students' learning styles: A longitudinal
Nurse education today, 31(5):444–449, 2011.

[229]
Kristin Annabel Torjussen Folland.
viSQLizer: An interactive visualizer for learning SQL.
Master's thesis, 2016.

[230]
Mary Forehand.
Bloom’s taxonomy.
Emerging perspectives on learning, teaching, and technology,
41(4):47–56, 2010.

[231]
Elvis C Foster and Shripad Godbole.
Overview of SQL.
In Database Systems, pages 205–209. Springer, 2016.

[232]
Neil Fraser.
Ten things we've learned from Blockly.
In 2015 IEEE Blocks and Beyond Workshop (Blocks and Beyond),
pages 49–50. IEEE, 2015.

[233]
Jeffrey EF Friedl.
Mastering regular expressions.
“O'Reilly Media, Inc.", 2006.

[234]
Rongrong Fu, Hong Wang, and Wenbo Zhao.
Dynamic driver fatigue detection using hidden Markov model in real
driving condition.
Expert Systems with Applications, 63:397–411, 2016.

[235]
Karen Furst, William W Lang, and Daniel E Nolle.
Internet banking.
Journal of Financial Services Research, 22(1-2):95–117, 2002.

[236]
Mark Gales, Steve Young, et al.
The application of hidden Markov models in speech recognition.
Foundations and Trends® in Signal Processing,
1(3):195–304, 2008.

[237]
Neelamadhav Gantayat, Diptikalyan Saha, Jaydeep Sen, and Senthil Mani.
Goal-based ontology creation for natural language querying in sap-erp
In Proceedings of the ACM India Joint International Conference
on Data Science and Management of Data, pages 231–237. ACM, 2019.

[238]
Pierre Ganty and Pedro Valero.
Regular expression search on compressed text.
In 2019 Data Compression Conference (DCC), pages 528–537.
IEEE, 2019.

[239]
Chong-zhi Gao, Qiong Cheng, Pei He, Willy Susilo, and Jin Li.
Privacy-preserving naive Bayes classifiers secure against the
substitution-then-comparison attack.
Information Sciences, 444:72–88, 2018.

[240]
Hector Garcia-Molina and Kenneth Salem.
Main memory database systems: An overview.
IEEE Transactions on Knowledge & Data Engineering,
(6):509–516, 1992.

[241]
Matt Gardner, Joel Grus, Mark Neumann, Oyvind Tafjord, Pradeep Dasigi, Nelson
Liu, Matthew Peters, Michael Schmitz, and Luke Zettlemoyer.
AllenNLP: A deep semantic natural language processing platform.
arXiv preprint arXiv:1803.07640, 2018.

[242]
Philip Garner and John Amedeo Mariani.
Learning SQL in steps.
Journal on Systemics, Cybernetics and Informatics,
13(4):19–24, 2015.

[243]
Stuart Garner.
Learning resources and tools to aid novices learn programming.
In Informing science & information technology education joint
conference (INSITE), pages 213–222, 2003.

[244]
Nicholas Genise, Craig Gentry, Shai Halevi, Baiyu Li, and Daniele Micciancio.
Homomorphic encryption for finite automata.
IACR Cryptology ePrint Archive, 2019:176, 2019.

[245]
Dedre Gentner and Albert L Stevens.
Mental models.
Psychology Press, 2014.

[246]
Ridhima Ghai, Sakshum Kumar, and Avinash Chandra Pandey.
Spam detection using rating and review processing method.
In Smart Innovations in Communication and Computational
Sciences, pages 189–198. Springer, 2019.

[247]
Joseph Yossi Gil and Keren Lenz.
Simple and safe SQL queries with C++ templates.
In Proceedings of the 6th International Conference on Generative
Programming and Component Engineering, pages 13–24. ACM, 2007.

[248]
Navdeep Singh Gill.
Overview of artificial intelligence and natural language
processing, 2019.

[249]
Alessandra Giordani.
Mapping natural language into SQL in a NLIDB.
In International Conference on Application of Natural Language
to Information Systems, pages 367–371. Springer, 2008.

[250]
D Glas, Satoru Satake, Takayuki Kanda, and Norihiro Hagita.
An interaction design framework for social robots.
In Robotics: Science and Systems, volume 7, page 89, 2012.

[251]
Josue Espinosa Godinez and Hasan M Jamil.
Meet Cyrus-the Query by Voice mobile assistant for the tutoring
and formative assessment of SQL learners.
arXiv preprint arXiv:1811.04160, pages 1–6, 2018.

[252]
Rahul Goel, Shachi Paul, and Dilek Hakkani-Tür.
Hyst: A hybrid approach for flexible and accurate dialogue state
arXiv preprint arXiv:1907.00883, 2019.

[253]
Vaibhav Gogte, Aasheesh Kolli, Michael J Cafarella, Loris D'Antoni, and
Thomas F Wenisch.
Hare: Hardware accelerator for regular expressions.
In The 49th Annual IEEE/ACM International Symposium on
Microarchitecture, page 44. IEEE Press, 2016.

[254]
Yoav Goldberg and Michael Elhadad.
splitSVM: Fast, space-efficient, non-heuristic, polynomial kernel
computation for NLP applications.
In Proceedings of ACL-08: HLT, Short Papers, pages 237–240,

[255]
Phil Gooch.
BADREX: In situ expansion and coreference of biomedical
abbreviations using dynamic regular expressions.
arXiv preprint arXiv:1206.4522, 2012.

[256]
Ian Goodfellow, Yoshua Bengio, and Aaron Courville.
Deep learning.
MIT press, 2016.

[257]
Michael E Gorman.
Types of knowledge and their roles in technology transfer.
The Journal of Technology Transfer, 27(3):219–231, 2002.

[258]
Palash Goyal, Sumit Pandey, and Karan Jain.
Deep learning for natural language processing.
Apress, Berkeley, 2018.

[259]
Jan Goyvaerts.
Regular Expressions: The Complete Tutorial.
Lulu Press, 2006.

[260]
Burton Grad.
Relational database management systems: The formative years [guest
editor's introduction].
IEEE Annals of the History of Computing, 34(4):7–8, 2012.

[261]
Arthur C Graesser, Mark W Conley, and Andrew Olney.
Intelligent tutoring systems.

[262]
Carole Gray and Julian Malins.
Visualizing research: A guide to the research process in art and
Routledge, 2016.

[263]
Margaret E Gredler.
Learning and instruction: Theory into practice.
Macmillan New York, 1992.

[264]
Bert F Green Jr, Alice K Wolf, Carol Chomsky, and Kenneth Laughery.
Baseball: an automatic question-answerer.
In Papers presented at the May 9-11, 1961, western joint
IRE-AIEE-ACM computer conference, pages 219–224. ACM, 1961.

[265]
Gregory Grefenstette, Anne Schiller, and Salah Aït-Mokhtar.
Recognizing lexical patterns in text.
In Lexicon Development for Speech and Language Processing,
pages 141–168. Springer, 2000.

[266]
Andreas Grillenberger and Torsten Brinda.
eledSQL: a new web-based learning environment for teaching
databases and SQL at secondary school level.
In Proceedings of the 7th Workshop in Primary and Secondary
Computing Education, pages 101–104. ACM, 2012.

[267]
James R Groff, Paul N Weinberg, et al.
SQL: the complete reference, volume 2.
McGraw-Hill/Osborne, 2002.

[268]
Cornelia S Große and Alexander Renkl.
Finding and fixing errors in worked examples: Can this foster
learning outcomes?
Learning and Instruction, 17(6):612–634, 2007.

[269]
Shuchi Grover, Roy Pea, and Stephen Cooper.
Designing for deeper learning in a blended computer science course
for middle school students.
Computer Science Education, 25(2):199–237, 2015.

[270]
Dick Grune, Kees Van Reeuwijk, Henri E Bal, Ceriel JH Jacobs, and Koen
Modern compiler design.
Springer Science & Business Media, 2012.

[271]
Torsten Grust and Marc H Scholl.
How to comprehend queries functionally.
Journal of Intelligent Information Systems, 12(2-3):191–218,

[272]
Mario Guimaraes.
The kennesaw database courseware (kdc): strong points, weak points,
and experience using it in a classroom environment.
Journal of Computing Sciences in Colleges, 21(3):91–96, 2006.

[273]
Sumit Gulwani, José Hernández-Orallo, Emanuel Kitzelmann, Stephen H
Muggleton, Ute Schmid, and Benjamin Zorn.
Inductive programming meets the real world.
Communications of the ACM, 58(11):90–99, 2015.

[274]
Carlos Gussenhoven and Haike Jacobs.
Understanding phonology.
Routledge, 2017.

[275]
Sepand Haghighi, Masoomeh Jasemi, Shaahin Hessabi, and Alireza Zolanvari.
Pycm: Multiclass confusion matrix library in Python.
J. Open Source Software, 3(25):729, 2018.

[276]
S. Haiduc, J. Aponte, and A. Marcus.
Supporting program comprehension with source code summarization.
ACM/IEEE 32nd International Conference on Software Engineering,
2:223–226, 2010.

[277]
John Hale.
A probabilistic earley parser as a psycholinguistic model.
In Proceedings of the second meeting of the North American
Chapter of the Association for Computational Linguistics on Language
technologies, pages 1–8. Association for Computational Linguistics, 2001.

[278]
James Hamilton, Manuel Gonzalez Berges, Jean-Charles Tournier, and Brad
Scada statistics monitoring using the elastic stack (elasticsearch,
logstash, kibana).

[279]
Bo Han, Paul Cook, and Timothy Baldwin.
unimelb: Spanish text normalisation.
In Tweet Normalisation Workshop at Sociedad Espanola para el
Procesamiento del Lenguaje Natural (SEPLN), pages 32–36, 2013.

[280]
John D Hansen and Justin Reich.
Democratizing education? examining access and usage patterns in
massive open online courses.
Science, 350(6265):1245–1248, 2015.

[281]
Michael Hanus and Julia Krone.
A typeful integration of SQL into curry.
arXiv preprint arXiv:1701.00631, 2017.

[282]
Linda Harasim.
Learning theory and online technologies.
Routledge, 2017.

[283]
Cynthia Harden.
Regular expressions for IT men.

[284]
Guy Harrison.
Languages and programming interfaces.
In Next Generation Databases, pages 167–190. Springer, 2015.

[285]
Ibrahim Abaker Targio Hashem, Ibrar Yaqoob, Nor Badrul Anuar, Salimah Mokhtar,
Abdullah Gani, and Samee Ullah Khan.
The rise of “big data” on cloud computing: Review and open
research issues.
Information Systems, 47:98–115, 2015.

[286]
Zahra Hatami.
Towards an understanding of the mental model process while writing
SQL queries.

[287]
Pedram Hayati, Vidyasagar Potdar, Alex Talevski, Nazanin Firoozeh, Saeed
Sarenche, and Elham A Yeganeh.
Definition of spam 2.0: New spamming boom.
In 4th IEEE International Conference on Digital Ecosystems and
Technologies, pages 580–584. IEEE, 2010.

[288]
George E Hein.
The constructivist museum.
The educational role of the museum, 2:73–79, 1999.

[289]
Tobias Heinroth and Wolfgang Minker.
Introducing spoken dialogue systems into Intelligent
Springer Science & Business Media, 2012.

[290]
Jon Heller.
Modify data with advanced DML.
In Pro Oracle SQL Development, pages 191–218. Springer,

[291]
Jon Heller.
Understand relational databases.
In Pro Oracle SQL Development, pages 3–28. Springer, 2019.

[292]
Jon Heller.
Write large SQL statements.
In Pro Oracle SQL Development, pages 309–325. Springer, 2019.

[293]
John Hewitt and Christopher D Manning.
A structural probe for finding syntax in word representations.
In Proceedings of the 2019 Conference of the North American
Chapter of the Association for Computational Linguistics: Human Language
Technologies, Volume 1 (Long and Short Papers), pages 4129–4138, 2019.

[294]
Geoffrey Hinton, Li Deng, Dong Yu, George Dahl, Abdel-rahman Mohamed, Navdeep
Jaitly, Andrew Senior, Vincent Vanhoucke, Patrick Nguyen, Brian Kingsbury,
et al.
Deep neural networks for acoustic modeling in speech recognition.
IEEE Signal processing magazine, 29, 2012.

[295]
Julia Hirschberg and Christopher D Manning.
Advances in natural language processing.
Science, 349(6245):261–266, 2015.

[296]
Lynette Hirschman and Robert Gaizauskas.
Natural language question answering: the view from here.
natural language engineering, 7(4):275–300, 2001.

[297]
Jeannine St Pierre Hirtle.
Social constructivism.
English Journal, 85(1):91, 1996.

[298]
Cindy E Hmelo-Silver.
Problem-based learning: What and how do students learn?
Educational psychology review, 16(3):235–266, 2004.

[299]
Duc Tam Hoang, Minh Le Nguyen, and Son Bao Pham.
L2S: Transforming natural language questions into SQL queries.
In 2015 Seventh International Conference on Knowledge and
Systems Engineering, pages 85–90. IEEE, 2015.

[300]
Rex Hogan.
A practical guide to database design.
Chapman and Hall/CRC, 2018.

[301]
Natasa Hoic-Bozic, Vedran Mornar, and Ivica Boticki.
A blended learning approach to course design and implementation.
IEEE Transactions on Education, 52(1):19–30, 2009.

[302]
Peter Honey, Alan Mumford, et al.
The manual of learning styles.

[303]
Ilana Seidel Horn, Brette Garner, Britnie Delinger Kane, and Jason Brasel.
A taxonomy of instructional learning opportunities in teachers’
workgroup conversations.
Journal of Teacher Education, 68(1):41–54, 2017.

[304]
Ionel Alexandru Hosu, Radu Cristian Alexandru Iacob, Florin Brad, Stefan
Ruseti, and Traian Rebedea.
Natural language interface for databases using a Dual-Encoder
In Proceedings of the 27th International Conference on
Computational Linguistics, pages 514–524, 2018.

[305]
Matthew B Hoy.
Alexa, Siri, Cortana, and more: an introduction to voice
Medical reference services quarterly, 37(1):81–88, 2018.

[306]
Helen H Hu and Tricia D Shepherd.
Using POGIL to help students learn to program.
ACM Transactions on Computing Education (TOCE), 13(3):13, 2013.

[307]
Ying Hu, Seema Sundara, and Jagannathan Srinivasan.
Supporting time-constrained SQL queries in Oracle.
In Proceedings of the 33rd International Conference on very
Large Databases, pages 1207–1218. VLDB Endowment, 2007.

[308]
Chaochao Huang, Xipeng Qiu, and Xuanjing Huang.
Text classification with document embeddings.
In Chinese Computational Linguistics and Natural Language
Processing Based on Naturally Annotated Big Data, pages 131–140. Springer,

[309]
James Huang, Stephanie Rogers, and Eunkwang Joo.
Improving restaurants by extracting subtopics from Yelp reviews.
iConference 2014 (Social Media Expo), 2014.

[310]
Xuedong Huang, James Baker, and Raj Reddy.
A historical perspective of speech recognition.
Communications of the ACM, 57(1):94–103, 2014.

[311]
Ting-Hao Kenneth Huang, Walter S Lasecki, and Jeffrey P Bigham.
Guardian: A crowd-powered spoken dialog system for web apis.
In Third AAAI conference on human computation and
crowdsourcing, 2015.

[312]
Mark Hughes, I Li, Spyros Kotoulas, and Toyotaro Suzumura.
Medical text classification using convolutional neural networks.
Stud Health Technol Inform, 235:246–250, 2017.

[313]
David Hung.
Theories of learning and computer-mediated instructional
Educational Media International, 38(4):281–287, 2001.

[314]
Beth Hurst, Randall Wallace, and Sarah B Nixon.
The impact of social interaction on student learning.
Reading Horizons, 52(4):5, 2013.

[315]
William John Hutchins and Harold L Somers.
An introduction to machine translation, volume 362.
Academic Press London, 1992.

[316]
William John Hutchins.
Machine translation: past, present, future.
Ellis Horwood Chichester, 1986.

[317]
Ismaila Idris, Ali Selamat, Ngoc Thanh Nguyen, Sigeru Omatu, Ondrej Krejcar,
Kamil Kuca, and Marek Penhaker.
A combined negative selection algorithm–particle swarm optimization
for an email spam detection system.
Engineering Applications of Artificial Intelligence, 39:33–44,

[318]
Jane Iedemska, Gianluca Stringhini, Richard Kemmerer, Christopher Kruegel, and
Giovanni Vigna.
The tricks of the trade: What makes spam campaigns successful?
In 2014 IEEE Security and Privacy Workshops, pages 77–83.
IEEE, 2014.

[319]
Andre Inge.
Hidden Markov models.

[320]
Katherine Ireland.
The Bloomberg terminal: Mission critical or a “very expensive
Harvard Business School Open Forum, Harvard Business School,

[321]
Walaa Saber Ismail and Masun Nabhan Homsi.
DAWQAS: A dataset for Arabic why question answering system.
Procedia computer science, 142:123–131, 2018.

[322]
Peter Jackson and Isabelle Moulinier.
Natural language processing for online applications.
John Benjamins, 2007.

[323]
Paul S Jacobs.
Text-based intelligent systems: Current research and practice in
information extraction and retrieval.
Psychology Press, 2014.

[324]
Gerhard Jäger and James Rogers.
Formal language theory: refining the chomsky hierarchy.
Philosophical Transactions of the Royal Society B: Biological
Sciences, 367(1598):1956–1970, 2012.

[325]
Mary James.
Assessment, teaching and theories of learning.
Assessment and learning, 47:60, 2006.

[326]
Hasan M Jamil.
Knowledge rich natural language queries over structured biological
In Proceedings of the 8th ACM International Conference on
Bioinformatics, Computational Biology, and Health Informatics, pages
352–361. ACM, 2017.

[327]
Hitkul Jangid, Shivangi Singhal, Rajiv Ratn Shah, and Roger Zimmermann.
Aspect-based financial sentiment analysis using deep learning.
In Companion Proceedings of the The Web Conference 2018, pages
1961–1966. International World Wide Web Conferences Steering Committee,

[328]
Bernard J Jansen, Danielle Booth, and Brian Smith.
Using the taxonomy of cognitive learning to model online searching.
Information Processing & Management, 45(6):643–663, 2009.

[329]
Faizan Javed.
Techniques for Context-Free Grammar Induction and Applications:
Application of novel inference algorithms to software maintenance problems.
VDM Verlag, 2009.

[330]
Tony Jenkins.
On the difficulty of learning to program.
In Proceedings of the 3rd Annual Conference of the LTSN Centre
for Information and Computer Sciences, volume 4, pages 53–58. Citeseer,

[331]
Colin G Johnson and Ursula Fuller.
Is Bloom's taxonomy appropriate for computer science?
In Proceedings of the 6th Baltic Sea conference on Computing
education research: Koli Calling 2006, pages 120–123. ACM, 2006.

[332]
W Lewis Johnson and Elliot Soloway.
PROUST: Knowledge-based program understanding.
IEEE Transactions on Software Engineering, (3):267–275, 1985.

[333]
Philip N Johnson-Laird.
Mental models and human reasoning.
Proceedings of the National Academy of Sciences,
107(43):18243–18250, 2010.

[334]
Kiku Jones, Lori NK Leonard, and Guido Lang.
Desired skills for entry level IS positions: Identification and
Journal of Computer Information Systems, pages 1–7, 2016.

[335]
Timothée Jost, Nabil Ouerhani, Roman Von Wartburg, René Müri, and
Heinz Hügli.
Assessing the contribution of color in visual attention.
Computer Vision and Image Understanding, 100(1-2):107–123,

[336]
Biing Hwang Juang and Laurence R Rabiner.
Hidden Markov models for speech recognition.
Technometrics, 33(3):251–272, 1991.

[337]
Thanakrit Julavanich, Srinual Nalintippayawong, and Kanokwan
RSQLg: The reverse SQL question generation algorithm.
In 2019 IEEE 6th International Conference on Industrial
Engineering and Applications (ICIEA), pages 908–912. IEEE, 2019.

[338]
Jan Jungbluth, Rolf Krieger, Wolfgang Gerke, and Peter Plapper.
Combining virtual and robot assistants - a case study about
integrating Amazon's Alexa as a voice interface in robotics.
In Robotix-Academy Conference for Industrial Robotics, page 5.
Shaker, 2018.

[339]
Dan Jurafsky and Christopher Manning.
Natural language processing.
Instructor, 212(998):3482, 2012.

[340]
Dan Jurafsky.
Speech & language processing.
Pearson Education India, 2000.

[341]
Shaidah Jusoh and Hejab M Alfawareh.
Techniques, applications and challenging issue in text mining.
International Journal of Computer Science Issues (IJCSI),
9(6):431, 2012.

[342]
Cody Kalina and KC Powell.
Cognitive and social constructivism: Developing tools for an
effective classroom.
Education, 130(2):241–250, 2009.

[343]
Eliezer Kantorowitz.
Verbal use case specifications for informal requirements elicitation.
In Building Bridges: HCI, Visualization, and Non-formal
Modeling, pages 165–174. Springer, 2014.

[344]
Epaminondas Kapetanios.
Natural Language and Information Systems: 13th International
Conference on Applications of Natural Language to Information Systems, NLDB
2008 London, UK, June 24-27, 2008, Proceedings, volume 5039.
Springer Science & Business Media, 2008.

[345]
Arnav Kapur, Shreyas Kapur, and Pattie Maes.
Alterego: A personalized wearable silent speech interface.
In 23rd International Conference on Intelligent User
Interfaces, pages 43–53. ACM, 2018.

[346]
Juhani Karhumäki.
Automata and formal languages, 2007.

[347]
Jarkko Kari.
Automata and formal languages.
Fall semester, 2013.

[348]
Adi Katz and Ronit Shmallo.
Learning from errors as a pedagogic approach for reaching a higher
conceptual level in database modeling.
In International Conference on Advanced Information Systems
Engineering, pages 93–102. Springer, 2016.

[349]
Jalal Kawash.
Formulating second-order logic conditions in SQL.
In Proceedings of the 15th Annual Conference on Information
technology education, pages 115–120. ACM, 2014.

[350]
R Kearns, Stephen Shead, and Alan Fekete.
A teaching system for SQL.
In Proceedings of the 2nd Australasian conference on Computer
science education, pages 224–231. ACM, 1997.

[351]
Daniel A Keim, Florian Mansmann, Jörn Schneidewind, Jim Thomas, and Hartmut
Visual analytics: Scope and challenges.
In Visual data mining, pages 76–90. Springer, 2008.

[352]
Mayank Kejriwal, Jiayuan Ding, Runqi Shao, Anoop Kumar, and Pedro Szekely.
Flagit: A system for minimally supervised human trafficking indicator
arXiv preprint arXiv:1712.03086, 2017.

[353]
Ryan O Kellems, Terisa P Gabrielsen, and Caroline Williams.
Using visual organizers and technology: Supporting executive
function, abstract language comprehension, and social learning.
In Technology and the Treatment of Children with Autism Spectrum
Disorder, pages 75–86. Springer, 2016.

[354]
Alex Kendall and Yarin Gal.
What uncertainties do we need in Bayesian deep learning for
computer vision?
In Advances in neural information processing systems, pages
5574–5584, 2017.

[355]
Mary Anne Kennan, Fletcher Cole, Patricia Willard, and C.S Wilson.
Changes in the workplace: transformation of the information
In 2nd Research Applications in Information and Library Studies
Seminar, Canberra, pages 1–19, 2005.

[356]
Eamonn Keogh.
Naive Bayes classifier.

[357]
Veton Këpuska and Gamal Bohouta.
Comparing speech recognition systems (microsoft api, google api and
cmu sphinx).
Int. J. Eng. Res. Appl, 7(03):20–24, 2017.

[358]
Vlado Keselj.
Speech and Language Processing Pearson Prentice Hall,

[359]
Pegah Khosravi, Ehsan Kazemi, Marcin Imielinski, Olivier Elemento, and Iman
Deep convolutional neural networks enable discrimination of
heterogeneous digital pathology images.
EBioMedicine, 27:317–328, 2018.

[360]
Diksha Khurana, Aditya Koli, Kiran Khatter, and Sukhdev Singh.
Natural language processing: State of the art, current trends and
arXiv preprint arXiv:1708.05148, 2017.

[361]
Anvar N Khuziakhmetov and Galina V Porchesku.
Teaching listening comprehension: Bottom-up approach.
International journal of environmental and science education,
11(8):1989–2001, 2016.

[362]
Ian M Kinchin.
Visualising knowledge structures in biology: Discipline, curriculum
and student understanding.
Journal of Biological Education, 45(4):183–189, 2011.

[363]
Danil Kirillov.
Clustering Spam Emails Using Hadoop and FP-Trees.
PhD thesis, Carleton University, 2017.

[364]
Anthony Kleerekoper and Andrew Schofield.
SQL tester: an online SQL assessment tool and its impact.
In Proceedings of the 23rd Annual ACM Conference on Innovation
and Technology in Computer Science Education, pages 87–92. ACM, 2018.

[365]
Guillaume Klein, Yoon Kim, Yuntian Deng, Jean Senellart, and Alexander M Rush.
Opennmt: Open-source toolkit for neural machine translation.
arXiv preprint arXiv:1701.02810, 2017.

[366]
Ewan Klein.
Computational semantics in the natural language toolkit.
In Proceedings of the Australasian Language Technology Workshop
2006, pages 26–33, 2006.

[367]
Richard Klein.
The Wits Intelligent Teaching System (WITS): A smart lecture
theatre to assess audience engagement.
PhD thesis, 2006.

[368]
Carsten Kleiner, Christopher Tebbe, and Felix Heine.
Automated grading and tutoring of SQL statements to improve student
In Proceedings of the 13th Koli Calling International Conference
on Computing Education Research, pages 161–168. ACM, 2013.

[369]
Donald E. Knuth.
Computer Programming as an Art.
Communications of the ACM, 17(12):667–673, 1974.

[370]
Donald E. Knuth.
Big Omicron and Big Omega and Big Theta.
SIGACT News, 8(2):18–24, 1976.

[371]
Philipp Koehn and Rebecca Knowles.
Six challenges for neural machine translation.
arXiv preprint arXiv:1706.03872, 2017.

[372]
Philipp Koehn, Hieu Hoang, Alexandra Birch, Chris Callison-Burch, Marcello
Federico, Nicola Bertoldi, Brooke Cowan, Wade Shen, Christine Moran, Richard
Zens, et al.
Moses: Open source toolkit for statistical machine translation.
In Proceedings of the 45th annual meeting of the association for
computational linguistics companion volume proceedings of the demo and poster
sessions, pages 177–180, 2007.

[373]
Andreas Kokkalis, Panagiotis Vagenas, Alexandros Zervakis, Alkis Simitsis,
Georgia Koutrika, and Yannis Ioannidis.
Logos: a system for translating queries into narratives.
In Proceedings of the ACM SIGMOD International Conference on
Management of Data, pages 673–676. ACM, 2012.

[374]
Marcel Kornacker, Alexander Behm, Victor Bittorf, Taras Bobrovytsky, Casey
Ching, Alan Choi, Justin Erickson, Martin Grund, Daniel Hecht, Matthew
Jacobs, et al.
Impala: A modern, open-source SQL engine for Hadoop.
In 7th Biennial Conference on Innovative Data Systems Research,
volume 1, page 9, 2015.

[375]
Mykhailo Kotov.
NLP resources for a rare language morphological analyzer: Danish
In Computational linguistics and intelligent systems (COLINS
2017). National Technical University «KhPI»,

[376]
Paula Kotzé, Karen Renaud, and Judy van Biljon.
Don’t do this–pitfalls in using anti-patterns in teaching
human–computer interaction principles.
Computers & Education, 50(3):979–1008, 2008.

[377]
Guy Leonard Kouemou and Dr Przemyslaw Dymarski.
History and theoretical basics of hidden Markov models.
Hidden Markov Models, Theory and Applications, 1, 2011.

[378]
David R Krathwohl and Lorin W Anderson.
A taxonomy for learning, teaching, and assessing: A revision of
Bloom's taxonomy of educational objectives.
Longman, 2001.

[379]
David R Krathwohl.
A revision of Bloom's taxonomy: An overview.
Theory into practice, 41(4):212–218, 2002.

[380]
Jennifer Kreie and Bruce A Ernst.
From database concepts to application: Use problem-based learning and
Oracle development tools to facilitate learning.
In Proceedings of the Information Systems Educators Conference,
volume 2167, page 1435. Citeseer, 2013.

[381]
Zbyněk Křivka and Alexander Meduna.
Jumping grammars.
International Journal of Foundations of Computer Science,
26(06):709–731, 2015.

[382]
Stephan Krusche, Bruce Scharlau, Åsa Cajander, and Janet Hughes.
50 years of software engineering: challenges, results, and
opportunities in its education.
In Proceedings of the 23rd Annual ACM Conference on Innovation
and Technology in Computer Science Education, pages 362–363. ACM, 2018.

[383]
Logan Kugler.
Being recognized everywhere.
Communications of the ACM, 62(2):17–19, 2019.

[384]
Vipin Kumar and Laveen N Kanal.
The CDP: A unifying formulation for heuristic search, dynamic
programming, and branch-and-bound.
In Search in Artificial Intelligence, pages 1–27. Springer,

[385]
T Kumaresan and C Palanisamy.
E-mail spam classification using s-cuckoo search and support vector
International Journal of Bio-Inspired Computation,
9(3):142–156, 2017.

[386]
Orna Kupferman.
Automata theory and model checking.
In Handbook of Model Checking, pages 107–151. Springer, 2018.

[387]
Youngsung Kwon, Alexis Kwasinski, and Andres Kwasinski.
Solar irradiance forecast using naïve Bayes classifier based
on publicly available weather forecasting variables.
Energies, 12(8):1529, 2019.

[388]
Charalampos Kyfonidis, Nektarios Moumoutzis, and Stavros Christodoulakis.
Block-C: A block-based programming teaching tool to facilitate
introductory C programming courses.
In Global Engineering Education Conference (EDUCON), 2017 IEEE,
pages 570–579. IEEE, 2017.

[389]
Sheldon J Lachman.
Learning is a process: Toward an improved definition of learning.
The Journal of psychology, 131(5):477–480, 1997.

[390]
Essi Lahtinen, Kirsti Ala-Mutka, and Hannu-Matti Järvinen.
A study of the difficulties of novice programmers.
In ACM SIGSCE Bulletin, volume 37, pages 14–18. ACM, 2005.

[391]
Essi Lahtinen.
A categorization of novice programmers: A cluster analysis study.
In PPIG, volume 16, pages 32–41, 2007.

[392]
Jennifer Lai, Clare-Marie Karat, and Nicole Yankelovich.
Conversational speech interfaces and technologies.
The Human-Computer Interaction Handbook,, pages 381–391, 2008.

[393]
H Chad Lane.
Cognitive models of learning.
Encyclopedia of the sciences of learning, pages 608–610, 2012.

[394]
Diana Laurillard.
Teaching as a design science: Building pedagogical patterns for
learning and technology.
Routledge, 2013.

[395]
Dejan Lavbič, Tadej Matek, and Aljaž Zrnec.
Recommender system for learning SQL using hints.
Interactive Learning Environments, 25(8):1048–1064, 2017.

[396]
Ramon Lawrence.
Integration and virtualization of relational SQL and NoSQL
systems including mySQL and MongoDB.
In 2014 International Conference on Computational Science and
Computational Intelligence, volume 1, pages 285–290. IEEE, 2014.

[397]
Yann LeCun, Yoshua Bengio, and Geoffrey Hinton.
Deep learning.
nature, 521(7553):436, 2015.

[398]
Yun Young Lee, Nicholas Chen, and Ralph E Johnson.
Drag-and-drop refactoring: intuitive and efficient program
In Proceedings of the 2013 International Conference on Software
Engineering, pages 23–32. IEEE Press, 2013.

[399]
Geoffrey Neil Leech.
100 million words of English: the British National Corpus

[400]
Wendy G Lehnert and Martin H Ringle.
Strategies for natural language processing.
Psychology Press, 2014.

[401]
Enrica Lemut, Benedict DuBoulay, and Giuliana Dettori.
Cognitive models and intelligent environments for learning
programming, volume 111.
Springer Science & Business Media, 2013.

[402]
Stanley Letovsky.
Cognitive processes in program comprehension.
Journal of Systems and software, 7(4):325–339, 1987.

[403]
Mark Levene and George Loizou.
A guided tour of relational databases and beyond.
Springer Science & Business Media, 2012.

[404]
Samuel J Levulis, Patricia R DeLucia, and So Young Kim.
Effects of touch, voice, and multimodal input, and task load on
multiple - UAV monitoring performance during simulated manned-unmanned
teaming in a military helicopter.
Human factors, 60(8):1117–1129, 2018.

[405]
Fei Li and Hosagrahar V Jagadish.
NaLIR: an interactive natural language interface for querying
relational databases.
In Proceedings of the ACM SIGMOD international conference on
Management of data, pages 709–712. ACM, 2014.

[406]
Fei Li and HV Jagadish.
Constructing an interactive natural language interface for relational
Proceedings of the VLDB Endowment, 8(1):73–84, 2014.

[407]
Fei Li and HV Jagadish.
Understanding natural language queries over relational databases.
ACM Special Interest Group on Management of Data Record,
45(1):6–13, 2016.

[408]
Yunyao Li, Rajasekar Krishnamurthy, Sriram Raghavan, Shivakumar Vaithyanathan,
and HV Jagadish.
Regular expression learning for information extraction.
In Proceedings of the Conference on Empirical Methods in Natural
Language Processing, pages 21–30. Association for Computational
Linguistics, 2008.

[409]
Linlin Li, Benjamin Roth, and Caroline Sporleder.
Topic models for word sense disambiguation and token-based idiom
In Proceedings of the 48th Annual Meeting of the Association for
Computational Linguistics, pages 1138–1147. Association for Computational
Linguistics, 2010.

[410]
Jiwei Li, Will Monroe, Alan Ritter, Michel Galley, Jianfeng Gao, and Dan
Deep reinforcement learning for dialogue generation.
arXiv preprint arXiv:1606.01541, 2016.

[411]
Tong Li, Jin Li, Zheli Liu, Ping Li, and Chunfu Jia.
Differentially private naive Bayes learning over multiple data
Information Sciences, 444:89–104, 2018.

[412]
Jingjing Li, Wenlu Wang, Wei-Shinn Ku, Yingtao Tian, and Haixun Wang.
SpatialNLI: A spatial domain natural language interface to
databases using spatial comprehension.
arXiv preprint arXiv:1908.10917, 2019.

[413]
Jesse Liberty.
Programming C#: Building. NET Applications with C.
" O'Reilly Media, Inc.", 2005.

[414]
Elizabeth D Liddy.
Natural language processing.

[415]
Henry Lieberman, Fabio Paternò, Markus Klann, and Volker Wulf.
End-user development: An emerging paradigm.
In End user development, pages 1–8. Springer, 2006.

[416]
Wei Ying Lim, Angela Ong, Lay Lian Soh, and Adam Sufi.
Teachers’ voices and change: The structure and agency dialectics
that shaped teachers’ pedagogy toward deep learning.
In Future learning in primary schools, pages 147–158.
Springer, 2016.

[417]
Yuming Lin, Tao Zhu, Hao Wu, Jingwei Zhang, Xiaoling Wang, and Aoying Zhou.
Towards online anti-opinion spam: Spotting fake reviews from the
review sequence.
In 2014 IEEE/ACM International Conference on Advances in Social
Networks Analysis and Mining (ASONAM 2014), pages 261–264. IEEE, 2014.

[418]
Peter Linz.
An introduction to formal languages and automata.
Jones & Bartlett Publishers, 2011.

[419]
Pierre Lison and Casey Kennington.
Opendial: A toolkit for developing spoken dialogue systems with
probabilistic rules.
In Proceedings of ACL-2016 System Demonstrations, pages 67–72,

[420]
David C Littman, Jeannine Pinto, Stanley Letovsky, and Elliot Soloway.
Mental models and software maintenance, Papers presented at the
first workshop on empirical studies of programmers on Empirical studies of
programmers (Norwood, NJ, USA), 1986.

[421]
Xia Liu, Lai C Liu, Kai S Koong, and June Lu.
An examination of job skills posted on Internet databases:
Implications for information systems degree programs.
Journal of Education for Business, 78(4):191–196, 2003.

[422]
Chen-Chung Liu, Yuan-Bang Cheng, and Chia-Wen Huang.
The effect of simulation games on the learning of computational
problem solving.
Computers & Education, 57(3):1907–1918, 2011.

[423]
Weibo Liu, Zidong Wang, Xiaohui Liu, Nianyin Zeng, Yurong Liu, and Fuad E
A survey of deep neural network architectures and their applications.
Neurocomputing, 234:11–26, 2017.

[424]
Qian Liu, Bei Chen, Jian-Guang Lou, Ge Jin, and Dongmei Zhang.
Fanda: A novel approach to perform follow-up query analysis.
arXiv preprint arXiv:1901.08259, 2019.

[425]
Mykhailo Lobur, AnDriy Romanyuk, and Mariana Romanyshyn.
Using nltk for educational and scientific purposes.
In 2011 11th international conference the experience of
designing and application of CAD systems in microelectronics (CADSM), pages
426–428. IEEE, 2011.

[426]
Edward Loper and Steven Bird.
NLTK: the natural language toolkit.
arXiv preprint cs/0205028, 2002.

[427]
Gustavo López, Luis Quesada, and Luis A Guerrero.
Alexa vs. Siri vs. Cortana vs. Google assistant: A
comparison of speech-based natural user interfaces.
In International Conference on Applied Human Factors and
Ergonomics, pages 241–250. Springer, 2017.

[428]
Klara Lorenz, Paul P Freddolino, Adelina Comas-Herrera, Martin Knapp, and
Jacqueline Damant.
Technology-based tools and services for people with dementia and
carers: Mapping technology onto the dementia care pathway.
Dementia, 18(2):725–741, 2019.

[429]
Matthew X Lowe, Ryan A Stevenson, Kristin E Wilson, Natasha E Ouslis, Morgan D
Barense, Jonathan S Cant, and Susanne Ferber.
Sensory processing patterns predict the integration of information
held in visual working memory.
Journal of Experimental Psychology: Human Perception and
Performance, 42(2):294, 2016.

[430]
Meiyu Lu, Srinivas Bangalore, Graham Cormode, Marios Hadjieleftheriou, and
Divesh Srivastava.
A dataset search engine for the research document corpus.
In 2012 IEEE 28th International Conference on Data Engineering,
pages 1237–1240. IEEE, 2012.

[431]
Amalia Luque, Alejandro Carrasco, Alejandro Martín, and Ana de las Heras.
The impact of class imbalance in classification performance metrics
based on the binary confusion matrix.
Pattern Recognition, 91:216–231, 2019.

[432]
Andrew Luxton-Reilly, Ibrahim Albluwi, Brett A Becker, Michail Giannakos,
Amruth N Kumar, Linda Ott, James Paterson, Michael James Scott, Judy Sheard,
Claudia Szabo, et al.
Introductory programming: a systematic literature review.
In Proceedings Companion of the 23rd Annual ACM Conference on
Innovation and Technology in Computer Science Education, pages 55–106. ACM,

[433]
Sze Yee Lye and Joyce Hwee Ling Koh.
Review on teaching and learning of computational thinking through
programming: What is next for k-12?
Computers in Human Behavior, 41:51–61, 2014.

[434]
Gabriel Lyons, Vinh Tran, Carsten Binnig, Ugur Cetintemel, and Tim Kraska.
Making the case for Query by Voice with Echoquery.
In Proceedings of the 2016 International Conference on
Management of Data, pages 2129–2132. ACM, 2016.

[435]
Nitin Madnani.
Getting started on natural language processing with Python.
ACM Crossroads, 13(4):5, 2007.

[436]
Lakshmana Phaneendra Maguluri, R Ragupathy, Sita Rama Krishna Buddi, Vamshi
Ponugoti, and Tharun Sai Kalimil.
Adaptive prediction of spam emails: Using Bayesian inference.
In 2019 3rd International Conference on Computing Methodologies
and Communication (ICCMC), pages 628–632. IEEE, 2019.

[437]
Frank H Maier and Andreas Größler.
What are we talking about?—a taxonomy of computer simulations to
support learning.
System Dynamics Review: The Journal of the System Dynamics
Society, 16(2):135–148, 2000.

[438]
David J Malan and Henry H Leitner.
Scratch for budding computer scientists.
In ACM Special Interest Group on Computer Science Education
Bulletin, volume 39, pages 223–227. ACM, 2007.

[439]
Linda Mannila, Valentina Dagiene, Barbara Demo, Natasa Grgurina, Claudio
Mirolo, Lennart Rolandsson, and Amber Settle.
Computational thinking in k-9 education.
In Proceedings of the working group reports of the 2014 on
innovation & technology in computer science education conference, pages
1–29. ACM, 2014.

[440]
Christopher D Manning, Christopher D Manning, and Hinrich Schütze.
Foundations of statistical natural language processing.
MIT press, 1999.

[441]
Christopher Manning, Prabhakar Raghavan, and Hinrich Schütze.
Introduction to information retrieval.
Natural Language Engineering, 16(1):100–103, 2010.

[442]
Christopher Manning, Mihai Surdeanu, John Bauer, Jenny Finkel, Steven Bethard,
and David McClosky.
The Stanford CoreNLP natural language processing toolkit.
In Proceedings of 52nd annual meeting of the association for
computational linguistics: system demonstrations, pages 55–60, 2014.

[443]
Christopher Manning.
Natural language processing.
In Proceedings of 52nd Annual Meeting of the Association for
Computational Linguistics: System Demonstrations, pages 55–60. Citeseer,

[444]
Christopher D Manning.
Computational linguistics and deep learning.
Computational Linguistics, 41(4):701–707, 2015.

[445]
Michael Mannino.
Database application development and design.
McGraw-Hill, Inc., 2001.

[446]
Ji-Ye Mao and Bradley R Brown.
The effectiveness of online task support vs. instructor-led training.
Contemporary Issues in End User Computing, page 77, 2007.

[447]
Mitchell Marcus, Grace Kim, Mary Ann Marcinkiewicz, Robert MacIntyre, Ann Bies,
Mark Ferguson, Karen Katz, and Britta Schasberger.
The penn treebank: annotating predicate argument structure.
In Proceedings of the workshop on Human Language Technology,
pages 114–119. Association for Computational Linguistics, 1994.

[448]
Ryan Marcus, Parimarjan Negi, Hongzi Mao, Chi Zhang, Mohammad Alizadeh, Tim
Kraska, Olga Papaemmanouil, and Nesime Tatbul.
Neo: A learned query optimizer.
arXiv preprint arXiv:1904.03711, 2019.

[449]
Anca Marginean.
Question answering over biomedical linked data with grammatical
Semantic Web, 8(4):565–580, 2017.

[450]
John C Martin.
Introduction to Languages and the Theory of Computation,
volume 4.
McGraw-Hill NY, 1991.

[451]
J.C. Martin.
Introduction to Languages and the Theory of Computation.
McGraw-Hill, New York, 2003.

[452]
Carolina Martins, Tiago Oliveira, and Aleš Popovič.
Understanding the Internet banking adoption: A unified theory of
acceptance and use of technology and perceived risk application.
International Journal of Information Management, 34(1):1–13,

[453]
Raina Mason, Carolyn Seton, and Graham Cooper.
Applying cognitive load theory to the redesign of a conventional
database systems course.
Computer Science Education, 26(1):68–87, 2016.

[454]
Bastien Maubert and Sophie Pinchinat.
Jumping automata for uniform strategies.
In IARCS Annual Conference on Foundations of Software Technology
and Theoretical Computer Science (FSTTCS 2013). Schloss
Dagstuhl-Leibniz-Zentrum fuer Informatik, 2013.

[455]
Richard E Mayer and Patricia A Alexander.
Handbook of research on learning and instruction.
Taylor & Francis, 2016.

[456]
Richard E Mayer.
Constructivism as a theory of learning versus constructivism as a
prescription for instruction.
Constructivist instruction: Success or failure, pages 184–200,

[457]
James McCann, Lea Albaugh, Vidya Narayanan, April Grow, Wojciech Matusik,
Jennifer Mankoff, and Jessica Hodgins.
A compiler for 3D machine knitting.
ACM Transactions on Graphics, 35(4):49, 2016.

[458]
Samuel D McDougle, Richard B Ivry, and Jordan A Taylor.
Taking aim at the cognitive side of learning in sensorimotor
adaptation tasks.
Trends in cognitive sciences, 20(7):535–544, 2016.

[459]
Monica McGill.
Critical skills for game developers: an analysis of skills sought by
In Proceedings of the 2008 conference on future play: Research,
play, share, pages 89–96. ACM, 2008.

[460]
Gregory McLeod.
Learning theory and instructional design.
Learning Matters, 2(3):35–43, 2003.

[461]
Michael F McTear.
Spoken dialogue technology: enabling the conversational user
ACM Computing Surveys (CSUR), 34(1):90–169, 2002.

[462]
Sean Mealin and Emerson Murphy-Hill.
An exploratory study of blind software developers.
In 2012 IEEE Symposium on Visual Languages and Human-Centric
Computing (VL/HCC), pages 71–74. IEEE, 2012.

[463]
Alexander Meduna and Ondřej Soukup.
Modern Language Models and Computation: Theory with
Springer, 2017.

[464]
Alexander Meduna and Petr Zemek.
Jumping finite automata.
International Journal of Foundations of Computer Science,
23(07):1555–1578, 2012.

[465]
Alexander Meduna and Petr Zemek.
Regulated Grammars and Automata.
Springer, 2014.

[466]
Alexander Meduna.
Formal Languages and Computation: Models and their
Auerbach Publications, 2014.

[467]
Jim Melton.
Database language SQL.
In Handbook on Architectures of Information Systems, pages
103–128. Springer, 1998.

[468]
Muhsin Menekse.
The reflection-informed learning and instruction to improve
students’ academic success in undergraduate classrooms.
The Journal of Experimental Education, pages 1–17, 2019.

[469]
Sharan B Merriam, Rosemary S Caffarella, and Lisa M Baumgartner.
Learning in adulthood: A comprehensive guide.
John Wiley & Sons, 2006.

[470]
Janet Metcalfe and Judy Xu.
Learning from one’s own errors and those of others.
Psychonomic Bulletin & Review, pages 1–7, 2017.

[471]
Janet Metcalfe.
Learning from errors.
Annual review of psychology, 68:465–489, 2017.

[472]
Farid Meziane, Nikos Athanasakis, and Sophia Ananiadou.
Generating natural language specifications from uml class diagrams.
Requirements Engineering, 13(1):1–18, 2008.

[473]
Daniel Miklody, Wendie M Uitterhoeve, Dimitri van Heel, Kerstin Klinkenberg,
and Benjamin Blankertz.
Maritime cognitive workload assessment.
10.1007/978-3-319-57753-1, 2017.

[474]
Alexander H Miller, Will Feng, Adam Fisch, Jiasen Lu, Dhruv Batra, Antoine
Bordes, Devi Parikh, and Jason Weston.
Parlai: A dialog research software platform.
arXiv preprint arXiv:1705.06476, 2017.

[475]
George A Miller.
WordNet: a lexical database for English.
Communications of the ACM, 38(11):39–41, 1995.

[476]
José Mira Mira.
Symbols versus connections: 50 years of artificial intelligence.
Neurocomputing, 71(4-6):671–680, 2008.

[477]
Amit Mishra and Sanjay Kumar Jain.
A survey on question answering systems with classification.
Journal of King Saud University-Computer and Information
Sciences, 28(3):345–361, 2016.

[478]
Antonija Mitrovic and Stellan Ohlsson.
Implementing CBM: SQL-tutor after fifteen years.
International Journal of Artificial Intelligence in Education,
26(1):150–159, 2016.

[479]
Antonija Mitrovic.
Learning SQL with a computerized tutor.
In ACM Special Interest Group on Computer Science Education
Bulletin, volume 30, pages 307–311. ACM, 1998.

[480]
Antonija Mitrovic.
An intelligent SQL tutor on the web.
International Journal of Artificial Intelligence in Education,
13(2-4):173–197, 2003.

[481]
Antonija Mitrovic.
Fifteen years of constraint-based tutors: what we have achieved and
where we are going.
User modeling and user-adapted interaction, 22(1-2):39–72,

[482]
Torben Ægidius Mogensen.
Basics of Compiler Design.
Torben Ægidius Mogensen, 2009.

[483]
Hussein Mohammed, Volker Mäergner, Thomas Konidaris, and H Siegfried
Normalised local naïve Bayes nearest-neighbour classifier for
offline writer identification.
In 2017 14th IAPR International Conference on Document Analysis
and Recognition (ICDAR), volume 1, pages 1013–1018. IEEE, 2017.

[484]
Mojgan Mohtashami and Julian M Scher.
Application of Bloom’s cognitive domain taxonomy to database
In Proceedings of ISECON (information systems educators
conference). Citeseer, 2000.

[485]
Ali Reza Montazemi and Hamed Qahri-Saremi.
Factors affecting adoption of online banking: A meta-analytic
structural equation modeling study.
Information & Management, 52(2):210–226, 2015.

[486]
Manju Mony, Jyothi M Rao, and Manish M Potey.
An overview of NLIDB approaches and implementation for airline
reservation system.
International Journal of Computer Applications, 107(5), 2014.

[487]
Jesús Moreno-León and Gregorio Robles.
Code to learn with scratch? a systematic literature review.
In 2016 IEEE Global Engineering Education Conference (EDUCON),
pages 150–156. IEEE, 2016.

[488]
Charles W Morris.
The pragmatic movement in american philosophy.

[489]
Hanspeter Mössenböck.
The Compiler Generator Coco/R User Manual.
pages 1–33, 2005.

[490]
Orval Mowrer.
Learning theory and behavior.

[491]
Regular Expression Language - Quick Reference: Microsoft
Developer Network Documentation on the .Net framework, version 4.5, regular
<https://msdn.microsoft.com/en-us/library/az24scfc(v=vs.110).aspx>, 2017.
Accessed: 2017-05-28.

[492]
Aminu Muhammad, Nirmalie Wiratunga, and Robert Lothian.
Contextual sentiment analysis for social media genres.
Knowledge-Based Systems, 108:92–101, 2016.

[493]
Dragos Stefan Munteanu and Daniel Marcu.
Improving machine translation performance by exploiting non-parallel
Computational Linguistics, 31(4):477–504, 2005.

[494]
Vamsi Krishna Myalapalli and Muddu Butchi Shiva.
An appraisal to optimize SQL queries.
In International Conference on Pervasive Computing), pages
1–6. IEEE, 2015.

[495]
Brad A Myers.
A brief history of human computer interaction technology.
interactions, 5(2):44–54, 1998.

[496]
Prakash M Nadkarni, Lucila Ohno-Machado, and Wendy W Chapman.
Natural language processing: an introduction.
Journal of the American Medical Informatics Association,
18(5):544–551, 2011.

[497]
Hiroyuki Nagataki, Yoshiaki Nakano, Midori Nobe, Tatsuya Tohyama, and Susumu
A visual learning tool for database operation.
In Proceedings of the 8th Workshop in Primary and Secondary
Computing Education, pages 39–40. ACM, 2013.

[498]
Albert Nagy and József Tick.
Improving transport management with big data analytics.
In IEEE 14th International Symposium on Intelligent Systems and
Informatics, pages 199–204. IEEE, 2016.

[499]
Amir Shareghi Najar, Antonija Mitrovic, and Bruce M McLaren.
Adaptive support versus alternating worked examples and tutored
problems: Which leads to better learning?
In International Conference on User Modeling, Adaptation, and
Personalization, pages 171–182. Springer, 2014.

[500]
Amir Shareghi Najar, Antonija Mitrovic, and Bruce M McLaren.
Learning with intelligent tutors and worked examples: selecting
learning activities adaptively leads to better learning outcomes than a fixed
User Modeling and User-Adapted Interaction, 26(5):459–491,

[501]
Toshiaki Nakazawa, Kun Yu, Daisuke Kawahara, and Sadao Kurohashi.
Example-based machine translation based on deeper NLP.
In International Workshop on Spoken Language Translation (IWSLT)
2006, 2006.

[502]
Jakub Náplava and Milan Straka.
CUNI system for the building educational applications 2019 shared
task: Grammatical error correction.
In Proceedings of the Fourteenth Workshop on Innovative Use of
NLP for Building Educational Applications, pages 183–190, 2019.

[503]
Vagheesh Narasimhan, Petr Danecek, Aylwyn Scally, Yali Xue, Chris Tyler-Smith,
and Richard Durbin.
BCFtools/RoH: a hidden Markov model approach for detecting
autozygosity from next-generation sequencing data.
Bioinformatics, 32(11):1749–1751, 2016.

[504]
Bonnie A. Nardi, Steve Whittaker, and Erin Bradner.
Interaction and outeraction: Instant messaging in action.
In Proceedings of the ACM Conference on Computer Supported
Cooperative Work, CSCW '00, pages 79–88, New York, NY, USA, 2000. ACM.

[505]
Tetsuya Nasukawa and Jeonghee Yi.
Sentiment analysis: Capturing favorability using natural language
In Proceedings of the 2nd international conference on Knowledge
capture, pages 70–77. ACM, 2003.

[506]
Markus Neteler, M Hamish Bowman, Martin Landa, and Markus Metz.
GRASS GIS: A multi-purpose open source GIS.
Environmental Modelling & Software, 31:124–130, 2012.

[507]
Thomas Neumann and Alfons Kemper.
Unnesting arbitrary queries.
Datenbanksysteme für Business, Technologie und Web (BTW
2015), 2015.

[508]
Hwee Tou Ng and Jin Kiat Low.
Chinese part-of-speech tagging: One-at-a-time or all-at-once?
word-based or character-based?
In Proceedings of the 2004 Conference on Empirical Methods in
Natural Language Processing, pages 277–284, 2004.

[509]
Hwee Tou Ng and John Zelle.
Corpus-based approaches to semantic interpretation in NLP.
AI magazine, 18(4):45–45, 1997.

[510]
Nhu H Nguyen, Zewei Song, Scott T Bates, Sara Branco, Leho Tedersoo, Jon Menke,
Jonathan S Schilling, and Peter G Kennedy.
Funguild: an open annotation tool for parsing fungal community
datasets by ecological guild.
Fungal Ecology, 20:241–248, 2016.

[511]
Mante S Nieuwland, Marte Otten, and Jos JA Van Berkum.
Who are you talking about? tracking discourse-level referential
processing with event-related brain potentials.
Journal of Cognitive Neuroscience, 19(2):228–236, 2007.

[512]
Neelu Nihalani, Sanjay Silakari, and Mahesh Motwani.
Natural language interface for database: a brief review.
International Journal of Computer Science Issues (IJCSI),
8(2):600, 2011.

[513]
Rachel Nordlinger and Louisa Sadler.
Morphology in lexical-functional grammar and head-driven phrase
structure grammar.
The Oxford handbook of morphological theory, 2019.

[514]
M Norouzifard, SH Davarpanah, MH Shenassa, et al.
Using natural language processing in order to create SQL queries.
In International Conference on Computer and Communication
Engineering, pages 600–604. IEEE, 2008.

[515]
George Obaido, Abejide Ade-Ibijola, and Hima Vadapalli.
Generating SQL queries from visual specifications.
In Communications in Computer and Information Science (CCIS),
pages 315–330, 2018.
Springer, Cham, Switzerland. ISBN: 978-3-030-05813-5. URL:

[516]
George Obaido, Abejide Ade-Ibijola, and Hima Vadapalli.
Generating narrations of nested SQL queries using context-free
In the proceedings of IEEE Conference on ICT and Society
(ICTAS), pages 1–6, 2019.
6th to 9th March, Durban. URL:
<https://ieeexplore.ieee.org/document/8703620>. [South Africa].

[517]
George Obaido, Abejide Ade-Ibijola, and Hima Vadapalli.
Synthesis of SQL queries from narrations.
In the proceedings of the 6th IEEE International Conference on
Soft Computing and Machine Intelligence (ISCMI 2019), pages 195–201, 2019.
ISBN: 978-1-7281-4576-1, November 19th to 20th, 2019 [South Africa].

[518]
George Obaido, Abejide Ade-Ibijola, and Hima Vadapalli.
TalkSQL: A tool for the synthesis of SQL queries from verbal
In the proceedings of the IEEE International Multidisciplinary
Information Technology and Engineering Conference (IMITEC 2019), pages
469–478, 2019.
November 21st to 22nd, 2019 [South Africa].

[519]
Stephen Obare, Abejide Ade-Ibijola, George Okeyo, and Kennedy Ogada.
Jumping finite automata for tweet comprehension.
In the proceedings of the IEEE International Multidisciplinary
Information Technology and Engineering Conference (IMITEC 2019),, pages
361–367, 2019.
November 21st to 22nd, 2019 [South Africa].

[520]
William C Ogden.
Implications of a cognitive model of database query: comparison of a
natural language, formal language and direct manipulation interface.
ACM SIGCHI Bulletin, 18(2):51–54, 1986.

[521]
Stellan Ohlsson.
Deep learning: How the mind overrides experience.
Cambridge University Press, 2011.

[522]
Nnamdi Ekene Okwunma.
Automatic comprehension of customer queries for feedback
generation, 2018.
MSc thesis.

[523]
Abdul-Majeed Omar.
Psychology of language acquisition and EFL teaching methodology: A
critical overview.
Gezira Journal of Educational Sciences and Humanities, 12(2),

[524]
Patrick O'neil.
DATABASE: principles programming performance.
Morgan Kaufmann, 2014.

[525]
Chorng-Shyong Ong, Min-Yuh Day, and Wen-Lian Hsu.
The measurement of user satisfaction with question answering systems.
Information & Management, 46(7):397–403, 2009.

[526]
Apache OpenNLP.
Apache software foundation.
URL http://opennlp.apache.org, 2011.

[527]
Damilola Orikogbo, Matthias Büchler, and Manuel Egele.
Crios: toward large-scale iOS application analysis.
In Proceedings of the 6th Workshop on Security and Privacy in
Smartphones and Mobile Devices, pages 33–42. ACM, 2016.

[528]
Alexandros Papangelis, Panagiotis Papadakos, Margarita Kotti, Yannis Stylianou,
Yannis Tzitzikas, and Dimitris Plexousakis.
Ld-sds: Towards an expressive spoken dialogue system based on
arXiv preprint arXiv:1710.02973, 2017.

[529]
Katerina Papantoniou and Yannis Tzitzikas.
Cs563-qa: A collection for evaluating question answering systems.
arXiv preprint arXiv:1907.01611, 2019.

[530]
Andrew J Park, Brian Beck, Darrick Fletche, Patrick Lam, and Herbert H Tsang.
Temporal analysis of radical dark web forum users.
In 2016 IEEE/ACM International Conference on Advances in Social
Networks Analysis and Mining (ASONAM), pages 880–883. IEEE, 2016.

[531]
Susan Pass.
When constructivists Jean Piaget and Lev Vygotsky were
pedagogical collaborators: A viewpoint from a study of their communications.
Journal of Constructivist Psychology, 20(3):277–282, 2007.

[532]
Rodolfo A Pazos R, Juan J González B, Marco A Aguirre L, José A
Martínez F, and Héctor J Fraire H.
Natural language interfaces to databases: an analysis of the state of
the art.
Recent Advances on Hybrid Intelligent Systems, pages 463–480,

[533]
Charles Sanders Peirce.
Logic as semiotic: The theory of signs.
Philosophical writings of Peirce, page 100, 1902.

[534]
Nanyun Peng, Francis Ferraro, Mo Yu, Nicholas Andrews, Jay DeYoung, Max Thomas,
Matthew R Gormley, Travis Wolfe, Craig Harman, Benjamin Van Durme, et al.
A concrete Chinese NLP pipeline.
In Proceedings of the 2015 Conference of the North American
Chapter of the Association for Computational Linguistics: Demonstrations,
pages 86–90, 2015.

[535]
Nancy Pennington.
Stimulus structures and mental representations in expert
comprehension of computer programs.
Cognitive psychology, 19(3):295–341, 1987.

[536]
Dominique Perrin.
Automata and formal languages.
Université de Marne-la-vallée, pages 1–22, 2003.

[537]
Brain Perry.
Advanced guide to the Bloomberg terminal: Bond market functions.
Investopedia Online, 2016.

[538]
Marian Petre and Alan F Blackwell.
Children as unwitting end-user programmers.
In IEEE Symposium on Visual Languages and Human-Centric
Computing, pages 239–242. IEEE, 2007.

[539]
Mary J Pickard et al.
The new Bloom’s taxonomy: An overview for family and consumer
Journal of Family and Consumer Sciences Education, 25(1), 2007.

[540]
Katarzyna Pisanski.
Human vocal communication of body size.
PhD thesis, 2014.

[541]
Lukasz Piwek and Adam Joinson.
“what do they snapchat about?” patterns of use in time-limited
instant messaging service.
Computers in Human Behavior, 54:358–367, 2016.

[542]
Diamanto Politis.
The process of entrepreneurial learning: a conceptual framework.
In Entrepreneurial Learning, pages 66–93. Routledge, 2008.

[543]
Ewoud Pons, Loes MM Braun, MG Myriam Hunink, and Jan A Kors.
Natural language processing in radiology: a systematic review.
Radiology, 279(2):329–343, 2016.

[544]
Julie Ponto.
Understanding and evaluating survey research.
Journal of the advanced practitioner in oncology, 6(2):168,

[545]
Emil L Post.
Recursively enumerable sets of positive integers and their decision
bulletin of the American Mathematical Society, 50(5):284–316,

[546]
Loreen M Powell and Hayden Wimmer.
Evaluating the effectiveness of self-created student screencasts as a
tool to increase student learning outcomes in a hands-on computer programming
Information Systems Education Journal, 13(5):106, 2015.

[547]
Linda Price.
Individual differences in learning: Cognitive control, cognitive
style, and learning style.
Educational Psychology, 24(5):681–698, 2004.

[548]
Julia Coleman Prior and Raymond Lister.
The backwash effect on SQL skills grading.
ACM Special Interest Group on Computer Science Education
Bulletin, 36(3):32–36, 2004.

[549]
Julia Coleman Prior.
Online assessment of SQL query formulation skills.
In Proceedings of the fifth Australasian conference on Computing
education-Volume 20, pages 247–256. Australian Computer Society, Inc.,

[550]
Julia R Prior.
AsseSQL: an online, browser-based SQL skills assessment tool.
In Proceedings of the Innovation & technology in computer
science education conference, pages 327–327. ACM, 2014.

[551]
Alan Pritchard.
Ways of learning: Learning theories for the classroom.
Routledge, 2017.

[552]
Sameerchand Pudaruth, Sandiana Amourdon, and Joey Anseline.
Automated generation of song lyrics using CFGs.
In 2014 Seventh International Conference on Contemporary
Computing (IC3), pages 613–616. IEEE, 2014.

[553]
Sean Pyott and Ian Sanders.
Alex: an aid to teaching algorithms.
ACM SIGCSE Bulletin, 23(3):36–44, 1991.

[554]
Xiaoguang Qi and Brian D Davison.
Web page classification: Features and algorithms.
ACM computing surveys (CSUR), 41(2):12, 2009.

[555]
Gang Qian.
Designing and implementing unsupervised online database labs.
Journal of Computing Sciences in Colleges, 27(4):30–36, 2012.

[556]
Xuedi Qin, Yuyu Luo, Nan Tang, and Guoliang Li.
DeepEye: Visualizing your data by keyword search.
In EDBT, pages 441–444, 2018.

[557]
Rao DV Raja.
Method and system for automatic switching between chat windows.
Google Patents, US Patent App. 13/738,785, 2014.

[558]
Pranav Rajpurkar, Jian Zhang, Konstantin Lopyrev, and Percy Liang.
Squad: 100,000+ questions for machine comprehension of text.
arXiv preprint arXiv:1606.05250, 2016.

[559]
Vennila Ramalingam and Susan Wiedenbeck.
An empirical study of novice program comprehension in the imperative
and object-oriented styles.
In the Seventh Workshop on Empirical studies of programmers,
pages 124–139. ACM, 1997.

[560]
Rodolfo A Pazos Rangel, Marco A Aguirre, Juan J González, and
Juan Martín Carpio.
Features and pitfalls that users should seek in natural language
interfaces to databases.
In Recent Advances on Hybrid Approaches for Designing
Intelligent Systems, pages 617–630. Springer, 2014.

[561]
Ashok Prasanna Rathinam and Ramani Sivakumar.
System and Method for Managing One or More Databases, 2011.
US Patent App. 12/634,844.

[562]
Shebuti Rayana and Leman Akoglu.
Collective opinion spam detection: Bridging review networks and
In Proceedings of the 21th acm sigkdd international conference
on knowledge discovery and data mining, pages 985–994. ACM, 2015.

[563]
Filbert Reinaldha and Tricya E Widagdo.
Natural language interfaces to database (NLIDB): Question handling
and unit conversion.
In 2014 International Conference on Data and Software
Engineering (ICODSE), pages 1–6. IEEE, 2014.

[564]
Phyllis Reisner.
Use of psychological experimentation as an aid to development of a
query language.
IEEE Transactions on Software Engineering, (3):218–229, 1977.

[565]
Ehud Reiter and Robert Dale.
Building natural language generation systems.
Cambridge university press, 2000.

[566]
Karen Renaud and H.A.S.
Facilitating efficacious transfer of database knowledge and skills.
In Ideas in Teaching, Learning and Assessment of Databases: A
Communication of the 7 th International Workshop on Teaching, Learning and
Assessment of Databases (TLAD 2009), pages 213–224. Springer, 2009.

[567]
Karen Renaud and Judy Van Biljon.
Teaching SQL—which pedagogical horse for this course?
In British National Conference on Databases, pages 244–256.
Springer, 2004.

[568]
Alexander Renkl.
Toward an instructionally oriented theory of example-based learning.
Cognitive science, 38(1):1–37, 2014.

[569]
Mitchel Resnick, John Maloney, Andrés Monroy-Hernández, Natalie Rusk,
Evelyn Eastmond, Karen Brennan, Amon Millner, Eric Rosenbaum, Jay Silver,
Brian Silverman, et al.
Scratch: programming for all.
Communications of the ACM, 52(11):60–67, 2009.

[570]
Mitchel Resnick.
Learn to code, code to learn.
EdSurge, May, 54, 2013.

[571]
Irina Rish et al.
An empirical study of the naive Bayes classifier.
In IJCAI 2001 workshop on empirical methods in artificial
intelligence, volume 3, pages 41–46, 2001.

[572]
Graeme D Ritchie, Graham J Russell, Alan W Black, and Stephen G Pulman.
Computational morphology: practical mechanisms for the English
MIT press, 1992.

[573]
Mona Rizvi, Thorna Humphries, Debra Major, Meghan Jones, and Heather Lauzun.
A CS0 course using Scratch.
Journal of Computing Sciences in Colleges, 26(3):19–27, 2011.

[574]
Brian Roark and Mark Johnson.
Efficient probabilistic top-down and left-corner parsing.
In Proceedings of the 37th annual meeting of the Association for
Computational Linguistics on Computational Linguistics, pages 421–428.
Association for Computational Linguistics, 1999.

[575]
Andrew Fiske Roberts, Craig W Stanfill, and Adam Harris Weiss.
Computer screen with visual programming icons, 2019.
US Patent App. 29/582,279.

[576]
Anthony Robins, Janet Rountree, and Nathan Rountree.
Learning and teaching programming: A review and discussion.
Computer science education, 13(2):137–172, 2003.

[577]
Emmanuel Roche and Yves Schabes.
Finite-state language processing.
MIT press, 1997.

[578]
Larry Rockoff.
The language of SQL.
Addison-Wesley Professional, 2016.

[579]
Ricardo Rodrigues, Hugo Gonçalo Oliveira, and Paulo Gomes.
NLPport: A pipeline for portuguese NLP (short paper).
In 7th Symposium on Languages, Applications and Technologies
(SLATE 2018). Schloss Dagstuhl-Leibniz-Zentrum fuer Informatik, 2018.

[580]
Rosa M Rodríguez, B Bedregal, Humberto Bustince, YC Dong, Bahram
Farhadinia, Cengiz Kahraman, L Martínez, Vicenç Torra, YJ Xu,
ZS Xu, et al.
A position and perspective analysis of hesitant fuzzy sets on
information fusion in decision making. towards high quality progress.
Information Fusion, 29:89–97, 2016.

[581]
Vidhu Rojit, Sindhu R Pai, Shruthi Kaivalya, and Viraj Kumar.
Visual specifications for web-application programming assignments.
In 2016 IEEE Eighth International Conference on Technology for
Education (T4E), pages 50–53. IEEE, 2016.

[582]
Chat Room.
Natural language processing.

[583]
Ariel Rosenfeld, Abejide Ade-Ibijola, and Sigrid Ewert.
Regex parser ii: teaching regular expression fundamentals via
educational gaming.
In Annual Conference of the Southern African Computer Lecturers'
Association, pages 99–112. Springer, 2017.

[584]
Pradeep Kumar Roy, Jyoti Prakash Singh, and Snehasish Banerjee.
Deep learning to filter SMS spam.
Future Generation Computer Systems, 2019.

[585]
Wei Ruan, Naveenkumar Appasani, Katherine Kim, Joseph Vincelli, Hyun Kim, and
Won-Sook Lee.
Pictorial visualization of emr summary interface and medical
information extraction of clinical notes.
In 2018 IEEE International Conference on Computational
Intelligence and Virtual Environments for Measurement Systems and
Applications (CIVEMSA), pages 1–6. IEEE, 2018.

[586]
Keijo Ruohonen.
Formal languages.
Lecture Notes, pages 1–94, 2009.

[587]
Nico Rutten, Wouter R Van Joolingen, and Jan T Van der Veen.
The learning effects of computer simulations in science education.
Computers & Education, 58(1):136–153, 2012.

[588]
James Owen Ryan, Eric Kaltman, Michael Mateas, and Noah Wardrip-Fruin.
What we talk about when we talk about games: Bottom-up game studies
using natural language processing.
Proc. FDG, 2015.

[589]
Serguei Saavedra, Kathleen Hagerty, and Brian Uzzi.
Synchronicity, instant messaging, and performance among financial
Proceedings of the National Academy of Sciences,
108(13):5296–5301, 2011.

[590]
Earl D Sacerdoti.
Language access to distributed data with error recovery.
Technical report, SRI International Menlo Park CA, Artificial
Intelligence Center, 1977.

[591]
Shazia Sadiq, Maria Orlowska, Wasim Sadiq, and Joe Lin.
SQLator: an online SQL learning workbench.
In ACM Special Interest Group on Computer Science Education
Bulletin, volume 36, pages 223–227. ACM, 2004.

[592]
Ivan A Sag, Timothy Baldwin, Francis Bond, Ann Copestake, and Dan Flickinger.
Multiword expressions: A pain in the neck for NLP.
In International Conference on Intelligent Text Processing and
Computational Linguistics, pages 1–15. Springer, 2002.

[593]
Seref Sagiroglu and Duygu Sinanc.
Big data: A review.
In International Conference on Collaboration Technologies and
Systems, pages 42–47. IEEE, 2013.

[594]
Diptikalyan Saha, Avrilia Floratou, Karthik Sankaranarayanan, Umar Farooq
Minhas, Ashish R Mittal, and Fatma Özcan.
Athena: an ontology-driven system for natural language querying over
relational data stores.
Proceedings of the VLDB Endowment, 9(12):1209–1220, 2016.

[595]
Sajal Saha, Mazid Alam, and Smita Dey.
A framework for artificially intelligent customized voice response
system design using speech synthesis markup.
Intelligent Speech Signal Processing, page 175, 2019.

[596]
Jatinderkumar R Saini and Rajnish M Rakholia.
On continent and script-wise divisions-based statistical measures for
stop-words lists of international languages.
Procedia Computer Science, 89:313–319, 2016.

[597]
Mayank Saini, Sharad Verma, and Aditi Sharan.
Multi-view ensemble learning using rough set based feature ranking
for opinion spam detection.
In Advances in Computer Communication and Computational
Sciences, pages 3–12. Springer, 2019.

[598]
Takeshi Sakaki, Fujio Toriumi, and Yutaka Matsuo.
Tweet trend analysis in an emergency situation.
In Proceedings of the Special Workshop on Internet and
Disasters, page 3. ACM, 2011.

[599]
Takeshi Sakaki, Masahide Okazaki, and Yoshikazu Matsuo.
Tweet analysis for real-time event detection and earthquake reporting
system development.
IEEE Transactions on Knowledge and Data Engineering,
25(4):919–931, 2013.

[600]
André Sander and Roland Wauer.
Integrating terminologies into standard SQL: a new approach for
research on routine data.
Journal of biomedical semantics, 10(1):7, 2019.

[601]
Romain Sandoz, Sarah Composto, Sandrine Divorne, Olivier Ertz, and Jens
GeoSQL Journey-A gamified learning experience to introduce (or
demystify) geospatial SQL queries.
Technical report, PeerJ Preprints, 2018.

[602]
Haniya Sarfraz.
Strategic leadership development: simplified with Bloom’s
Industrial and Commercial Training, 49(1):40–47, 2017.

[603]
Arvind Satyanarayan and Jeffrey Heer.
Lyra: An interactive visualization design environment.
In Computer Graphics Forum, volume 33, pages 351–360. Wiley
Online Library, 2014.

[604]
Ron Savage.
Database Language SQL (SQL-2003) SQL/Foundation.
<https://ronsavage.github.io/SQL/sql-2003-2.bnf.html>, 2017.
Accessed: 2018-09-30.

[605]
MS Schlager and William C Ogden.
A cognitive model of database querying: a tool for novice
ACM SIGCHI Bulletin, 17(4):107–113, 1986.

[606]
Sylvain Schmitz.
Approximating context-free grammars for parsing and
PhD thesis, Université Nice Sophia Antipolis, 2007.

[607]
Bernhard Schölkopf, Alexander J Smola, Francis Bach, et al.
Learning with kernels: support vector machines, regularization,
optimization, and beyond.
MIT press, 2002.

[608]
Carsten Schulte, Tony Clear, Ahmad Taherkhani, Teresa Busjahn, and James H
An introduction to program comprehension for computer science
In Proceedings of the 2010 ITiCSE working group reports, pages
65–86. ACM, 2010.

[609]
Dale H Schunk.
Learning theories an educational perspective sixth edition.
Pearson, 2012.

[610]
Kai Schweinsberg and Lutz Wegner.
Advantages of complex SQL types in storing XML documents.
Future Generation Computer Systems, 68:500–507, 2017.

[611]
Robert H Scott III.
Bloomberg 101.
Journal of Financial Education, pages 80–88, 2010.

[612]
Fabrizio Sebastiani.
Text categorization.
In Encyclopedia of Database Technologies and Applications,
pages 683–687. IGI Global, 2005.

[613]
Ahmed Seffah.
Patterns of HCI design and HCI design of patterns: bridging
HCI design and model-driven software engineering.
Springer, 2015.

[614]
Martin E Seligman.
On the generality of the laws of learning.
Psychological review, 77(5):406, 1970.

[615]
S Thamarai Selvi, P Karthikeyan, A Vincent, V Abinaya, G Neeraja, and
R Deepika.
Text categorization using rocchio algorithm and random forest
In 2016 Eighth International Conference on Advanced Computing
(ICoAC), pages 7–12. IEEE, 2017.

[616]
Subhasree Sengupta and Radhika Garg.
Impact of voice-based interaction on learning practices and behavior
of children.
In Joint Proceedings of the ACM IUI Workshops, Los Angeles, USA,
March 20, pages 1–3, 2019.

[617]
Iulian V Serban, Alessandro Sordoni, Yoshua Bengio, Aaron Courville, and Joelle
Building end-to-end dialogue systems using generative hierarchical
neural network models.
In Thirtieth AAAI Conference on Artificial Intelligence, 2016.

[618]
Iulian Vlad Serban, Alberto García-Durán, Caglar Gulcehre, Sungjin
Ahn, Sarath Chandar, Aaron Courville, and Yoshua Bengio.
Generating factoid questions with recurrent neural networks: The 30m
factoid question-answer corpus.
arXiv preprint arXiv:1603.06807, 2016.

[619]
Pieter Seuren.
Semantic syntax.
Brill, 2017.

[620]
Behrooz Seyed-Abbassi.
A SQL project as a learning method in a database course.
In Proceedings of the 1993 conference on Computer personnel
research, pages 291–297. ACM, 1993.

[621]
Seyyed Hossein Seyyedi and Behrouz Minaei-Bidgoli.
Estimator learning automata for feature subset selection in
high-dimensional spaces, case study: Email spam detection.
International Journal of Communication Systems, 31(8):e3541,

[622]
K Shabaz, Jim D O'Shea, Keeley A Crockett, and A Latham.
Aneesah: A conversational natural language interface to databases.
In Proceedings of the World Congress on Engineering, volume 1,

[623]
Russell L Shackelford.
Introduction to computing and algorithms.
Addison-Wesley Longman Publishing Co., Inc., 1997.

[624]
Hirav Shah and Amit Sengupta.
Designing mobile based computational support for low-literate
community health workers.
International Journal of Human-Computer Studies, 115:1–8,

[625]
Axita Shah, Jyoti Pareek, Hemal Patel, and Namrata Panchal.
NLKBIDB-natural language and keyword based interface to database.
In 2013 International conference on advances in computing,
communications and informatics (ICACCI), pages 1569–1576. IEEE, 2013.

[626]
Philipp Shah, Marc Berges, and Peter Hubwieser.
Qualitative content analysis of programming errors.
In Proceedings of the 5th International Conference on
Information and Education Technology, pages 161–166. ACM, 2017.

[627]
Subana Shanmuganathan.
Artificial neural network modelling: An introduction.
In Artificial Neural Network Modelling, pages 1–14. Springer,

[628]
Aakanksha Sharaff, Naresh Kumar Nagwani, and Abhishek Dhadse.
Comparative study of classification algorithms for spam email
In Emerging research in computing, information, communication
and applications, pages 237–244. Springer, 2016.

[629]
Amal Shargabi, Syed Ahmad Aljunid, Muthukkaruppanan Annamalai, Shuhaida Mohamed
Shuhidan, and Abdullah Mohd Zin.
Program comprehension levels of abstraction for novices.
In International Conference on Computer, Communications, and
Control Technology, pages 211–215. IEEE, 2015.

[630]
Lakshay Sharma, Laura Graesser, Nikita Nangia, and Utku Evci.
Natural language understanding with the quora question pairs dataset.
arXiv preprint arXiv:1907.01041, 2019.

[631]
L Sharmila and U Sakthi.
Chronological pattern exploration algorithm for gene expression data
clustering and classification.
Wireless Personal Communications, 102(2):1503–1519, 2018.

[632]
John Shawe-Taylor, Nello Cristianini, et al.
Kernel methods for pattern analysis.
Cambridge university press, 2004.

[633]
Saeedeh Shekarpour, Edgard Marx, Axel-Cyrille Ngonga Ngomo, and Sören Auer.
Sina: Semantic interpretation of user queries for question answering
on interlinked data.
Journal of Web Semantics, 30:39–51, 2015.

[634]
Brian Sheldon.
Cognitive-behavioural therapy: research and practice in health
and social care.
Routledge, 2011.

[635]
Peter B Sheridan.
The arithmetic translator-compiler of the IBM FORTRAN automatic
coding system.
Communications of the ACM, 2(2):9–21, 1959.

[636]
Ben Shneiderman.
Improving the human factors aspect of database interactions.
ACM Transactions on Database Systems (TODS), 3(4):417–439,

[637]
Ben Shneiderman.
Creating creativity: user interfaces for supporting innovation.
ACM Transactions on Computer-Human Interaction, 7(1):114–138,

[638]
Craig A Shue, Minaxi Gupta, John J Lubia, Chin Hua Kong, and Asim Yuksel.
Spamology: A study of spam origins.
In the 6th Conference on Email and Anti-Spam (CEAS), 2009.

[639]
Heung-Yeung Shum, Xiao-dong He, and Di Li.
From Eliza to XiaoIce: challenges and opportunities with social
Frontiers of Information Technology & Electronic Engineering,
19(1):10–26, 2018.

[640]
Keng Siau and Xin Tan.
Cognitive mapping techniques for user-database interaction.
IEEE transactions on professional communication, 49(2):96–108,

[641]
Yasin N Silva, Isadora Almeida, and Michell Queiroz.
SQL: From traditional databases to big data.
In Proceedings of the 47th ACM Technical Symposium on Computing
Science Education, pages 413–418. ACM, 2016.

[642]
Rishabh Singh, Sumit Gulwani, and Armando Solar-Lezama.
Automated feedback generation for introductory programming
ACM Special Interest Group on Programming Languages Notices,
48(6):15–26, 2013.

[643]
Arnab Sinha, Zhihong Shen, Yang Song, Hao Ma, Darrin Eide, Bo-june Paul Hsu,
and Kuansan Wang.
An overview of microsoft academic service (mas) and applications.
In Proceedings of the 24th international conference on world
wide web, pages 243–246. ACM, 2015.

[644]
Michael Sipser.
Introduction to the Theory of Computation, volume 2.
Thomson Course Technology Boston, 2006.

[645]
Richard Socher, Yoshua Bengio, and Christopher D Manning.
Deep learning for NLP (without magic).
In Tutorial Abstracts of ACL 2012, pages 5–5. Association for
Computational Linguistics, 2012.

[646]
Mario Soflano, Thomas M Connolly, and Thomas Hainey.
Learning style analysis in adaptive GBL application to teach SQL.
Computers & Education, 86:105–119, 2015.

[647]
Artem Sokolov, Julia Kreutzer, Christopher Lo, and Stefan Riezler.
Learning structured predictors from bandit feedback for interactive
In Proceedings of the 54th Annual Meeting of the Association for
Computational Linguistics (Volume 1: Long Papers), pages 1610–1620, 2016.

[648]
Elliot Soloway and Kate Ehrlich.
Empirical studies of programming knowledge.
IEEE Transactions on software engineering, (5):595–609, 1984.

[649]
Ian Sommerville.
Software Engineering.
Addison-Wesley, Boston, MA, USA, 10th edition, 2015.

[650]
Dezhao Song, Frank Schilder, Charese Smiley, Chris Brew, Tom Zielund, Hiroko
Bretz, Robert Martin, Chris Dale, John Duprey, Tim Miller, et al.
TR Discover: A natural language interface for querying and
analyzing interlinked datasets.
In International Semantic Web Conference, pages 21–37.
Springer, 2015.

[651]
Erik LL Sonnhammer, Gunnar Von Heijne, Anders Krogh, et al.
A hidden Markov model for predicting transmembrane helices in
protein sequences.
In Ismb, volume 6, pages 175–182, 1998.

[652]
Benjamin Sowell, Alan Demers, Johannes Gehrke, Nitin Gupta, Haoyuan Li, and
Walker White.
From declarative languages to declarative processing in computer
arXiv preprint arXiv:0909.1770, 2009.

[653]
Ahmet Soylu, Martin Giese, Ernesto Jimenez-Ruiz, Guillermo Vega-Gorgojo, and
Ian Horrocks.
Experiencing optiqueVQS: a multi-paradigm and ontology-based visual
query system for end users.
Universal Access in the Information Society, 15(1):129–152,

[654]
Ahmet Soylu, Martin Giese, Ernesto Jimenez-Ruiz, Evgeny Kharlamov, Dmitriy
Zheleznyakov, and Ian Horrocks.
Ontology-based end-user visual query formulation: Why, what, who,
how, and which?
Universal Access in the Information Society, 16(2):435–467,

[655]
Bhargav Srinivasa-Desikan.
Natural Language Processing and Computational Linguistics: A
practical guide to text analysis with Python, Gensim, spaCy, and
Packt Publishing Ltd, 2018.

[656]
Savitha Srinivasan and Eric Brown.
Is speech recognition becoming mainstream?
Computer, (4):38–41, 2002.

[657]
Christopher W Starr, Bill Manaris, and RoxAnn H Stalvey.
Bloom's taxonomy revisited: specifying assessable learning
objectives in computer science.
In ACM SIGCSE Bulletin, volume 40, pages 261–265. ACM, 2008.

[658]
Kamenka Staykova.
Natural language generation and semantic technologies.
Cybernetics and Information Technologies, 14(2):3–23, 2014.

[659]
Roger Alan Stein, Patricia A Jaques, and João Francisco Valiati.
An analysis of hierarchical text classification using word
Information Sciences, 471:216–232, 2019.

[660]
M-A Storey.
Theories, methods and tools in program comprehension: Past, present
and future.
In 13th International Workshop on Program Comprehension
(IWPC'05), pages 181–191. IEEE, 2005.

[661]
Margaret-Anne Storey.
Theories, tools and research methods in program comprehension: past,
present and future.
Software Quality Journal, 14(3):187–208, 2006.

[662]
Milan Straka and Jana Straková.
Tokenizing, PoS tagging, lemmatizing and parsing UD 2.0 with
In Proceedings of the CoNLL 2017 Shared Task: Multilingual
Parsing from Raw Text to Universal Dependencies, pages 88–99, 2017.

[663]
Pascal Sturmfels, Saige Rutherford, Mike Angstadt, Mark Peterson, Chandra
Sripada, and Jenna Wiens.
A domain guided CNN architecture for predicting age from structural
brain images.
arXiv preprint arXiv:1808.04362, 2018.

[664]
B Sujatha, Dr S Viswanadha Raju, and Humera Shaziya.
A survey of natural language interface to database management system.
International Journal of Science and Advance Technology,
2(6):56–61, 2012.

[665]
Chen Sun, Abhinav Shrivastava, Saurabh Singh, and Abhinav Gupta.
Revisiting unreasonable effectiveness of data in deep learning era.
In Proceedings of the IEEE international conference on computer
vision, pages 843–852, 2017.

[666]
Shiliang Sun, Chen Luo, and Junyu Chen.
A review of natural language processing techniques for opinion mining
Information fusion, 36:10–25, 2017.

[667]
Sukanya Suranauwarat.
An approach to solving technical difficulties facing non-CS
students in a database class.
International Journal of Modern Education and Computer Science,
9(2):14, 2017.

[668]
John Sweller.
Cognitive load during problem solving: Effects on learning.
Cognitive science, 12(2):257–285, 1988.

[669]
John Sweller.
The worked example effect and human cognition.
Learning and instruction, 16(2):165–169, 2006.

[670]
Soni Sweta and Kanhaiya Lal.
Learner model for automatic detection of learning style using FCM
in adaptive e-learning system.
IOSR Journal of Engineering, 18(2):18–24, 2016.

[671]
Toni Taipalus, Mikko Siponen, and Tero Vartiainen.
Errors and complications in SQL query formulation.
ACM Transactions on Computing Education (TOCE), 18(3):15, 2018.

[672]
Nassim Nicholas Taleb.
Antifragile: Things That Gain from Disorder (Incerto
Book 3).
Random House, New York, NY, USA, 2012.

[673]
Bo Tang, Haibo He, Paul M Baggenstoss, and Steven Kay.
A Bayesian classification approach using class-specific features
for text categorization.
IEEE Transactions on Knowledge and Data Engineering,
28(6):1602–1606, 2016.

[674]
Yichuan Tang.
Deep learning using linear support vector machines.
arXiv preprint arXiv:1306.0239, 2013.

[675]
Jenny A Thomas.
Meaning in interaction: An introduction to pragmatics.
Routledge, 2014.

[676]
Errol Thompson, Andrew Luxton-Reilly, Jacqueline L Whalley, Minjie Hu, and Phil
Bloom's taxonomy for CS assessment.
In Proceedings of the tenth conference on Australasian computing
education-Volume 78, pages 155–161. Australian Computer Society, Inc.,

[677]
P Thurley and R Dennick.
Problem-based learning and radiology.
Clinical radiology, 63(6):623–628, 2008.

[678]
Jenifer Tidwell.
Common ground: A pattern language for human-computer interface
design, 1999.

[679]
Jenifer Tidwell.
UI patterns and techniques.
Zdroj: www. mit. edu/ jtidwell, 2002.

[680]
Jenifer Tidwell.
Designing interfaces: Patterns for effective interaction
" O'Reilly Media, Inc.", 2010.

[681]
Abigail Tittizer and Venkatesan Ramamoorthy.
Systems and methods for managing data associated with computer
code, 2006.
US Patent App. 11/379,390.

[682]
Kenneth G Tobin.
Constructivism as a referent for teaching and learning.
In The practice of constructivism in science education, pages
19–38. Routledge, 2012.

[683]
Diego A Tobon-Mejia, Kamal Medjaher, Noureddine Zerhouni, and Gérard
Hidden Markov models for failure diagnostic and prognostic.
In 2011 Prognostics and System Health Managment Confernece,
pages 1–8. IEEE, 2011.

[684]
Zahra S Torabi, Mohammad H Nadimi-Shahraki, and Akbar Nabiollahi.
Efficient support vector machines for spam detection: a survey.
International Journal of Computer Science and Information
Security, 13(1):11, 2015.

[685]
Robert Lawrence Trask.
A dictionary of phonetics and phonology.