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Towards Modeling Student Engagement with Interactive Computing Textbooks: An Empirical Study

Published: 05 March 2021 Publication History

Abstract

Interactive textbooks have great potential to increase student engagement with the course content which is critical to effective learning in computing education. Prior research on digital textbooks and interactive visualizations contributes to our understanding of student interactions with visualizations and modeling textbook knowledge concepts. However, research investigating student usage of interactive computing textbooks is still lacking. This study seeks to fill this gap by modeling student engagement with a Jupyter-notebook-based interactive textbook. Our findings suggest that students' active interactions with the presented interactive textbook, including changing, adding, and executing code in addition to manipulating visualizations, are significantly stronger in predicting student performance than conventional reading metrics. Our findings contribute to a deeper understanding of student interactions with interactive textbooks and provide guidance on the effective usage of said textbooks in computing education.

References

[1]
Eric Fouh, Monika Akbar, and Clifford A Shaffer. The role of visualization in computer science education. Computers in the Schools, 29 (1--2): 95--117, 2012.
[2]
Shirley Booth. Learning computer science and engineering in context. Computer Science Education, 11 (3): 169--188, 2001.
[3]
Qiang Hao, Brad Barnes, Robert Maribe Branch, and Ewan Wright. Predicting computer science students? online help-seeking tendencies. Knowledge Management & E-Learning: An International Journal, 9 (1): 19--32, 2017.
[4]
David H Smith IV, Qiang Hao, Vanessa Dennen, Michail Tsikerdekis, Bradly Barnes, Lilu Martin, and Nathan Tresham. Towards understanding online question & answer interactions and their effects on student performance in large-scale stem classes. International Journal of Educational Technology in Higher Education, 17 (1): 1--15, 2020.
[5]
Andreas Holzinger, Michael Kickmeier-Rust, and Dietrich Albert. Dynamic media in computer science education; content complexity and learning performance: is less more? Journal of Educational Technology & Society, 11 (1), 2008.
[6]
Clifford A Shaffer, Matthew L Cooper, Alexander Joel D Alon, Monika Akbar, Michael Stewart, Sean Ponce, and Stephen H Edwards. Algorithm visualization: The state of the field. ACM Transactions on Computing Education (TOCE), 10 (3): 9, 2010.
[7]
005)]eckerdal2005noviceAnna Eckerdal and Michael Thuné. Novice java programmers' conceptions of" object" and" class", and variation theory. ACM SIGCSE Bulletin, 37 (3): 89--93, 2005.
[8]
David H Smith IV, Qiang Hao, Filip Jagodzinski, Yan Liu, and Vishal Gupta. Quantifying the effects of prior knowledge in entry-level programming courses. In Proceedings of the ACM Conference on Global Computing Education, pages 30--36. ACM, 2019.
[9]
and Mevz ek]pecorari2012readingDiane Pecorari, Philip Shaw, Aileen Irvine, Hans Malmström, and vS pela Mevz ek. Reading in tertiary education: Undergraduate student practices and attitudes. Quality in Higher Education, 18 (2): 235--256, 2012.
[10]
Fernando Perez and Brian E Granger. Project jupyter: Computational narratives as the engine of collaborative data science. Retrieved September, 11 (207): 108, 2015.
[11]
Adam Rule, Aurélien Tabard, and James D Hollan. Exploration and explanation in computational notebooks. In Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems, page 32. ACM, 2018.
[12]
Keith O'Hara, Douglas Blank, and James Marshall. Computational notebooks for ai education. In The Twenty-Eighth International Flairs Conference, 2015.
[13]
David B Daniel and William Douglas Woody. E-textbooks at what cost? performance and use of electronic v. print texts. Computers & Education, 62: 18--23, 2013.
[14]
pinar, and Ogata]boticki2019bookIvica Boticki, Gökhan Akcc apinar, and Hiroaki Ogata. E-book user modelling through learning analytics: the case of learner engagement and reading styles. Interactive Learning Environments, 27 (5--6): 754--765, 2019.
[15]
Khushboo Thaker, Yun Huang, Peter Brusilovsky, and He Daqing. Dynamic knowledge modeling with heterogeneous activities for adaptive textbooks. In The 11th International Conference on Educational Data Mining, pages 592--595, 2018.
[16]
Hemalatha Sasidharakurup, Rakhi Radhamani, Dhanush Kumar, Nijin Nizar, Krishnashree Achuthan, and Shyam Diwakar. Using virtual laboratories as interactive textbooks: Studies on blended learning in biotechnology classrooms. ICST Trans. e-Education e-Learning, 2 (6): e4, 2015.
[17]
Hiroaki Ogata, Chengjiu Yin, Misato Oi, Fumiya Okubo, Atsushi Shimada, Kentaro Kojima, and Masanori Yamada. E-book-based learning analytics in university education. In International Conference on Computer in Education (ICCE 2015), pages 401--406, 2015.
[18]
Alex Edgcomb, Frank Vahid, Roman Lysecky, Andre Knoesen, Rajeevan Amirtharajah, and Mary Lou Dorf. Student performance improvement using interactive textbooks: A three-university cross-semester analysis. In 2015 ASEE Annual Conference and Exposition, 2015.
[19]
Dawn McKinney, Alex Daniel Edgcomb, Roman Lysecky, and Frank Vahid. Improving pass rates by switching from a passive to an active learning textbook in cs0. In 2020 ASEE Virtual Annual Conference Experience, 2020.
[20]
Carrie Spencer. Research on learners' preferences for reading from a printed text or from a computer screen. Journal of Distance Education, 21 (1): 33--50, 2006.
[21]
Yoram Eshet-Alkalai and Nitza Geri. Does the medium affect the message? the influence of text representation format on critical thinking. Human Systems Management, 26 (4): 269--279, 2007.
[22]
Amanda J Rockinson-Szapkiw, Jennifer Courduff, Kimberly Carter, and David Bennett. Electronic versus traditional print textbooks: A comparison study on the influence of university students' learning. Computers & Education, 63: 259--266, 2013.
[23]
Reynol Junco and Candrianna Clem. Predicting course outcomes with digital textbook usage data. The Internet and Higher Education, 27: 54--63, 2015.
[24]
R Eric Landrum, Regan AR Gurung, and Nathan Spann. Assessments of textbook usage and the relationship to student course performance. College Teaching, 60 (1): 17--24, 2012.
[25]
Ronald Baecker. Sorting out sorting: A case study of software visualization for teaching computer science. Software visualization: Programming as a multimedia experience, 1: 369--381, 1998.
[26]
Marc H Brown and Robert Sedgewick. Techniques for algorithm animation. Ieee Software, (1): 28--39, 1985.
[27]
Christopher D Hundhausen, Sarah A Douglas, and John T Stasko. A meta-study of algorithm visualization effectiveness. Journal of Visual Languages & Computing, 13 (3): 259--290, 2002.
[28]
Christopher D Hundhausen and Jonathan L Brown. Designing, visualizing, and discussing algorithms within a cs 1 studio experience: An empirical study. Computers & Education, 50 (1): 301--326, 2008.
[29]
Juha Sorva, Ville Karavirta, and Lauri Malmi. A review of generic program visualization systems for introductory programming education. ACM Transactions on Computing Education (TOCE), 13 (4): 1--64, 2013.
[30]
ssling, Dann, Korhonen, Malmi, Rantakokko, Ross, et al.]naps2003evaluatingThomas Naps, Stephen Cooper, Boris Koldehofe, Charles Leska, Guido Rößling, Wanda Dann, Ari Korhonen, Lauri Malmi, Jarmo Rantakokko, Rockford J Ross, et al. Evaluating the educational impact of visualization. In Acm sigcse bulletin, volume 35, pages 124--136. ACM, 2003.
[31]
Benjamin Samuel Bloom. Taxonomy of educational objectives: the classification of educational goals: Handbook I, Cognitive domain. McKay, 1969.
[32]
Niko Myller, Roman Bednarik, Erkki Sutinen, and Mordechai Ben-Ari. Extending the engagement taxonomy: Software visualization and collaborative learning. ACM Transactions on Computing Education (TOCE), 9 (1): 1--27, 2009.
[33]
ssling et al.(2006)Rößling, Naps, Hall, Karavirta, Kerren, Leska, Moreno, Oechsle, Rodger, Urquiza-Fuentes, et al.]rossling2006mergingGuido Rößling, Thomas Naps, Mark S Hall, Ville Karavirta, Andreas Kerren, Charles Leska, Andrés Moreno, Rainer Oechsle, Susan H Rodger, Jaime Urquiza-Fuentes, et al. Merging interactive visualizations with hypertextbooks and course management. In ACM SIGCSE Bulletin, volume 38, pages 166--181. ACM, 2006.
[34]
qvist et al.(2016)F"arnqvist, Heintz, Lambrix, Mannila, and Wang]farnqvist2016supportingTommy F"arnqvist, Fredrik Heintz, Patrick Lambrix, Linda Mannila, and Chunyan Wang. Supporting active learning by introducing an interactive teaching tool in a data structures and algorithms course. In Proceedings of the 47th ACM Technical Symposium on Computing Science Education, pages 663--668, 2016.
[35]
Bradley N Miller and David L Ranum. Beyond pdf and epub: toward an interactive textbook. In Proceedings of the 17th ACM annual conference on Innovation and technology in computer science education, pages 150--155, 2012.
[36]
Barbara J Ericson, Mark J Guzdial, and Briana B Morrison. Analysis of interactive features designed to enhance learning in an ebook. In Proceedings of the eleventh annual International Conference on International Computing Education Research, pages 169--178, 2015.
[37]
Iman YeckehZaare, Paul Resnick, and Barbara Ericson. A spaced, interleaved retrieval practice tool that is motivating and effective. In Proceedings of the 2019 ACM Conference on International Computing Education Research, pages 71--79, 2019.
[38]
Juliet M. Corbin and Anselm L. Strauss. Basics of qualitative research: techniques and procedures for developing grounded theory. SAGE Publications, Inc., 2008.
[39]
David Furcy. Jhavepop: Visualizing linked-list operations in c
[40]
and java. Journal of Computing Sciences in Colleges, 25 (1): 32--41, 2009.
[41]
S Sriadhi, Robbi Rahim, and Ansari Saleh Ahmar. Rc4 algorithm visualization for cryptography education. In Journal of Physics: Conference Series, volume 1028, page 012057. IOP Publishing, 2018.
[42]
Naomi S Baron. Words onscreen: The fate of reading in a digital world. Oxford University Press, USA, 2015.
[43]
Yueh-Min Huang and Tsung-Ho Liang. A technique for tracking the reading rate to identify the e-book reading behaviors and comprehension outcomes of elementary school students. British Journal of Educational Technology, 46 (4): 864--876, 2015.
[44]
z, Granger, Bussonnier, Frederic, Kelley, Hamrick, Grout, Corlay, et al.]kluyver2016jupyterThomas Kluyver, Benjamin Ragan-Kelley, Fernando Pérez, Brian E Granger, Matthias Bussonnier, Jonathan Frederic, Kyle Kelley, Jessica B Hamrick, Jason Grout, Sylvain Corlay, et al. Jupyter notebooks-a publishing format for reproducible computational workflows. In ELPUB, pages 87--90, 2016.
[45]
Qiang Hao, David H Smith IV, Naitra Iriumi, Michail Tsikerdekis, and Amy J Ko. A systematic investigation of replications in computing education research. ACM Transactions on Computing Education (TOCE), 19 (4): 1--18, 2019.

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  • (2024)SuperNOVA: Design Strategies and Opportunities for Interactive Visualization in Computational NotebooksExtended Abstracts of the CHI Conference on Human Factors in Computing Systems10.1145/3613905.3650848(1-17)Online publication date: 11-May-2024
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    cover image ACM Conferences
    SIGCSE '21: Proceedings of the 52nd ACM Technical Symposium on Computer Science Education
    March 2021
    1454 pages
    ISBN:9781450380621
    DOI:10.1145/3408877
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    Published: 05 March 2021

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    Author Tags

    1. interaction behavior modeling
    2. interactive textbook
    3. jupyter notebook
    4. learning analytics
    5. visualization

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    View all
    • (2024)SuperNOVA: Design Strategies and Opportunities for Interactive Visualization in Computational NotebooksExtended Abstracts of the CHI Conference on Human Factors in Computing Systems10.1145/3613905.3650848(1-17)Online publication date: 11-May-2024
    • (2024)Digital competence and students’ engagement: a comprehensive analysis of smartphone utilization, perceived autonomy and formal digital learning as mediatorsInteractive Technology and Smart Education10.1108/ITSE-09-2023-018921:3(461-488)Online publication date: 15-Feb-2024
    • (2024)AIoT tool integration for enriching teaching resources and monitoring student engagementInternet of Things10.1016/j.iot.2023.10104526(101045)Online publication date: Jul-2024
    • (2024)Examples and tutorials on using Google Colab and Gradio to create online interactive student‐learning modulesComputer Applications in Engineering Education10.1002/cae.2272932:4Online publication date: 29-Feb-2024
    • (2023)Class Participation, Using Technology to Enhance Efficiency and Fairness2023 IEEE International Conference on Teaching, Assessment and Learning for Engineering (TALE)10.1109/TALE56641.2023.10398380(1-8)Online publication date: 28-Nov-2023
    • (2022)Which log variables significantly predict academic achievement? A systematic review and meta‐analysisBritish Journal of Educational Technology10.1111/bjet.1328254:1(142-191)Online publication date: 24-Oct-2022
    • (2022)Using Jupyter Tools to Design an Interactive Textbook to Guide Undergraduate Research in Materials InformaticsJournal of Chemical Education10.1021/acs.jchemed.2c0064099:10(3601-3606)Online publication date: 19-Sep-2022
    • (2021)Pedagogical conditions for using an interactive notebook as a means of developing the cognitive interest of younger schoolchildren in learning the Russian languageManagement of Education10.25726/a1337-6128-3582-r(196-212)Online publication date: 15-Oct-2021
    • (2021)Context-aware Execution Migration Tool for Data Science Jupyter Notebooks on Hybrid Clouds2021 IEEE 17th International Conference on eScience (eScience)10.1109/eScience51609.2021.00013(30-39)Online publication date: Sep-2021

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