Curriculum analytics of an Open Distance Learning (ODL) Programme: A data-driven perspective
Abstract
Student support, which is an integral part of a learning programme, is most effective when it is integrated into the design of the curricula, rather than when it forms stand-alone interventions. Identifying those areas that require attention from a student support perspective is often based on the perspectives of the institution and teaching staff involved, rather than on how Students concerned interact with the programme. In this article, we draw on the research fields of curriculum analytics to identify areas of curriculum improvement for an ODL programme using student data. The results of the study indicate the important role that is played by curriculum analytics in designing student support interventions, and in restructuring elements of the curriculum structure to support student success. Such is done by ascertaining what constitutes the learned curriculum versus the planned curriculum, the Temporal Distance between Courses, and any bottlenecks within the programme that might hamper progression. The results, further, underscore the need for an effective execution strategy to be aligned with the principles that guided the development of the curriculum concerned.
Downloads
References
Arafeh, Sousan. 2016. “Curriculum Mapping in Higher Education: A Case Study and Proposed Content Scope and Sequence Mapping Tool.” Journal of Further and Higher Education 40(5): 585–611. https://doi.org/10.1080/0309877X.2014.1000278.
Brown, Michael Geoffrey, R. Matthew DeMonbrun, and Stephanie D. Teasley. 2018a. “Conceptualizing Co-Enrollment: Accounting for Student Experiences Across the Curriculum.” In Proceedings of the 8th International Conference on Learning Analytics & Knowledge - LAK‘18, 305–309.
Brown, Michael Geoffrey, R. Matthew DeMonbrun, and Stephanie D. Teasley. 2018b. “Conceptualizing Co-Enrollment: Accounting for Student Experiences Across the Curriculum.” In LAK’18: International Conference on Learning Analytics and Knowledge, 305–309. Sydney, NSW, Australia: ACM. https://doi.org/https://doi.org/10.1145/3170358.3170366.
Dawson, Shane and Harry Hubball. 2014. “Curriculum analytics: Applications of social network analysis for improving strategic curriculum decision-making in a research-intensive university.” Teaching and Learning Inquiry 2(2): 59‒74. https://doi.org/10.20343/teachlearningu.2.2.59.
Dawson, Shane, Srecko Joksimovic, Oleksandra Poquet, and George Siemens. 2019. “Increasing the Impact of Learning Analytics.” In Proceedings of the International Conference on Learning Analytics and Knowledge. Arizona, USA: ACM. https://doi.org/10.1145/3303772.3303784.
De Freitas, Sara, David Gibson, Coert Du Plessis, Pat Halloran, Ed Williams, Matt Ambrose, Ian Dunwell, and Sylvester Arnab. 2015. “Foundations of Dynamic Learning Analytics: Using University Student Data to Increase Retention.” British Journal of Educational Technology 46(6): 1175–1188. https://doi.org/10.1111/bjet.12212.
Dunn, Kevin. 2019. Process Improvement Using Data. https://learnche.org/pid/.
Dutton, Ellen E. 2015. “The Implementation of Curriculum Mapping at a Private High School.” PhD. Diss. Walden University.
Great School Partnership. 2013. “Grade Point Average.” The Glossary of Education Reform.
Greer, Jim, Craig Thompson, Ryan Banow, and Stephanie Frost. 2016. “Data-Driven Programmatic Change at Universities: What Works and How.” In Proceedings of the 1st Learning Analytics for Curriculum and Program Quality Improvement Workshop, ed. Jim Greer, Marco Molinaro, Xavier Ochoa, and Timothy Mckay, 30–35. Edinburgh: Learning analytics and Knowledge.
Herodotou, Christothea, Bart Rienties, Martin Hlosta, Avinash Boroowa, and Chrysoula Mangafa. 2020. “The Scalable Implementation of Predictive Learning Analytics at a Distance Learning University: Insights from a Longitudinal Case Study.” The Internet and Higher Education 45: 100725. https://doi.org/10.1016/j.iheduc.2020.100725.
Hilliger, Isabel, Camila Aguirre, Constanza Miranda, Sergio Celis, and Mar Pérez-sanagustín. 2020. “Design of a Curriculum Analytics Tool to Support Continuous Improvement Processes in Higher Education.” In Proceedings of the 10th International Conferences on Learning Analytics and Knowledge (LAK’20), 181–186. Frankfurt, Germany: ACM. https://doi.org/https://doi.org/10.1145/3375462.3375489.
Huilgol, Shobha V. 2020. “Contextual Curriculum Planning: Tailoring Your Curriculum to the Local Context – An Overview.” AI Ameen J Med Scie 3(1): 1–4.
Joksimovic, Srecko, Dragan Gašević, Thomas M. Loughin, Vitomir Kovanovic, and Hatala Marek. 2015. “Learning at distance: Effects of interaction traces on academic achievement.” Computers & Education 87: 204‒217. https://doi.org/10.1016/j.compedu.2015.07.002.
Khan, Mohammad Ayub and Laurie Smith Law. 2015. “An Integrative Approach to Curriculum Development in Higher Education in the USA: A Theoretical Framework.” International Education Studies 8(3): 66–76. https://doi.org/10.5539/ies.v8n3p66.
Kitto, Kirsty, Nikhil Sarathy, Aleksandr Gromov, Ming Liu, Katarzyna Musial, and Simon Buckingham Shum. 2020. “Towards Skills-Based Curriculum Analytics: Can We Automate the Recognition of Prior Learning?” In Proceedings of the Tenth International Conference on Learning Analytics and Knowledge (LAK‘20), 171–180. Frankfurt, Germany: ACM. https://doi.org/https://dl.acm.org/doi/10.1145/3375462.3375526.
Krogh, Ellen, Ane Qvortrup, and Stefan Ting Graf. 2021. Didaktik and Curriculum in Ongoing Dialogue. Taylor & Francis. https://doi.org/10.4324/9781003099390-1.
Lonn, Steven, Thomas Brown, West Hall, Ann Arbor, Cinda-sue Davis, Darryl Koch, Chrysler Cntr, and Ann Arbor. 2014. “Customized Course Advising: Investigating Engineering Student Success with Incoming Profiles and Patterns of Concurrent Course Enrollment.” In LAK '14: Proceedings of the Fourth International Conference on Learning Analytics and Knowledge, 16–25.
Lunn, Stephanie, Jia Zhu, and Monique Ross. 2020. “Utilizing Web Scraping and Natural Language Processing to Better Inform Pedagogical Practice.” In Proceedings of the 2020 IEEE Frontiers in Education Conference. https://doi.org/10.1109/FIE44824.2020.9274270.
Mälkki, Helena and Jukka V. Paatero. 2015. “Curriculum Planning in Energy Engineering Education.” Journal of Cleaner Production 106: 292–299. https://doi.org/https://doi.org/10.1016/j.jclepro.2014.08.109.
Méndez, Gonzalo, Xavier Ochoa, and Katherine Chiluiza. 2014. “Techniques for Data-Driven Curriculum Analysis.” In Proceedings of the Fourth International Conference on Learning Analytics and Knowledge, 148–157. Indianapolis, IN, USA. https://doi.org/10.1145/2567574.2567591.
Mendez, Gonzalo, Xavier Ochoa, Katherine Chiluiza, and Bram de Wever. 2014. “Curricular Design Analysis: A Data-Driven Perspective.” Journal of Learning Analytics 1(3): 84–119. https://doi.org/10.18608/jla.2014.13.6.
Mevik, Bjørn-helge. 2004. “Mean Squared Error of Prediction (MSEP) Estimates for Principal Component Regression (PCR) and Partial Least Squares Regression (PLSR).” Journal of Chemometrics 18(9): 422–429.
Modebelu, Melody Ndidi. 2015. “Curriculum Development Models for Quality Educational System.” In Handbook of Research on Enhancing Teacher Education with Advanced Instructional Technologies, ed. Nwachukwu Prince Ololube, Peter James Kpolovie, and Lazarus Ndiku Makewa, 259–276. Hershey, PA: IGI Global. https://doi.org/10.4018/978-1-4666-8162-0.ch014.
Morsy, Sara and George Karypis. 2019. “A Study on Curriculum Planning and Its Relationship with Graduation GPA and Time To Degree.” In The 9th International Learning Analytics & Knowledge Conference (LAK19), 26–35. Tempe, AZ, USA: ACM. https://doi.org/ https://doi.org/10.1145/3303772.3303783.
O’Neill, Geraldine, Roisin Donnelly, and Marian Fitzmaurice. 2014. “Supporting Programme Teams to Develop Sequencing in Higher Education Curricula.” International Journal for Academic Development 19(4): 268–280. https://doi.org/10.1080/1360144X.2013.867266.
Ochoa, Xavier. 2016a. “Simple Metrics for Curricular Analytics.” In Proceedings of the 1 St Learning Analytics for Curriculum and Program Quality Improvement Workshop, 1590: 20–26.
Ochoa, Xavier. 2016b. “Simple Metrics for Curricular Analytics.” In CEUR Workshop Proceedings, Vol. 1590, 20–26. CEUR-WS.
Ornstein, A. C. and F. P. Hunkins. 2009. Curriculum Foundations, Principles and Issues. 5th ed. Boston, MA: Allyn & Bacon.
Pardos, Zachary A., Zihao Fan, and Weijie Jiang. 2019. “Connectionist Recommendation in the Wild: On the Utility and Scrutability of Neural Networds for Personalized Course Guidance.” User Modeling and User-Adapted Interaction 29: 487–525. https://doi.org/https://doi.org/10.1007/s11257-019-09218-7.
Patton, Anna Louise, and Krista L. Prince. 2018. “Curriculum Design and Planning: Using Postmodern Curriculum Approaches.” Journal of Curriculum Theorizing 32(3): 93–114.
Pereira, Jose, Srini Chary, Jeffrey B. Moat, Jonathan Faulkner, Nathalie Gravelle-Ray, Odete Carreira, Diana Vincze, et al. 2020. “Pallium Canada’s Curriculum Development Model: A Framework to Support Large-Scale Courseware Development and Deployment.” Journal of Palliative Medicine 23(6): 759–67. https://doi.org/10.1089/jpm.2019.0292.
Reiss, Philip T. and R. Todd Ogden. 2007. “Functional Principal Component Regression and Functional Partial Least Squares.” Journal of the American Statistical Association 102(479): 984–996. https://doi.org/10.1198/016214507000000527.
Shelton, Brett E., Jui-long Hung, and Patrick R. Lowenthal. 2017. “Predicting Student Success by Modeling Student Interaction in Asynchronous Online Courses.” Distance Education 38(1): 59–69. https://doi.org/10.1080/01587919.2017.1299562.
Siemens, George. 2013. “Learning Analytics: The Emergence of a Discipline.” American Behavioral Scientist 57(10): 1380–1400. https://doi.org/10.1177/0002764213498851.
Zhuhadar, Leyla, Jerry Daday, Scarlett Marklin, Bruce Kessler, and Tuesdi Helbig. 2019. “Using Survival Analysis to Discovering Pathways to Success in Mathematics.” Computers in Human Behavior 92: 487–95. https://doi.org/10.1016/j.chb.2017.12.016.
Copyright (c) 2021 Elias Oupa Mashile, Angelo Fynn, Matshepo Matoane
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
This journal is an open access journal, and the authors and journal should be properly acknowledged, when works are cited.
Authors, copyright holders, may use the publishers version for teaching purposes, in books, theses, dissertations, conferences and conference papers.
A copy of the authors' publishers version may also be hosted on the following websites:
- Non-commercial personal homepage or blog.
- Institutional webpage.
- Authors Institutional Repository.
The following notice should accompany such a posting on the website: This is an electronic version of an article published in SAJHE, Volume XXX, number XXX, pages XXX “XXX", DOI. Authors should also supply a hyperlink to the original paper or indicate where the original paper (http://www.journals.ac.za/index.php/SAJHE) may be found.
Authors publishers version, affiliated with the Stellenbosch University will be automatically deposited in the University Institutional Repository SUNScholar.
Articles as a whole, may not be re-published with another journal.
The following license applies:
Attribution CC BY-NC-ND 4.0
