- G. Siemens, and P. Long, “Penetrating the fog: Analytics in learning and education,” EDUCAUSE review, vol. 46, no. 5, pp. 30, 2011.Google Scholar
- S. Dawson, S. Joksimovic, O. Poquet, and G. Siemens, “Increasing the Impact of Learning Analytics,” in Ninth International Conference of Learning Analytics and Knowledge (LAK19), Tempe, Arizona, 2019.Google ScholarDigital Library
- L. P. Macfadyen, S. Dawson, A. Pardo, and D. Gaševic, “Embracing big data in complex educational systems: The learning analytics imperative and the policy challenge,” Research & Practice in Assessment, vol. 9, pp. 17-28, 2014.Google Scholar
- N. Selwyn, “What's the problem with learning analytics?,” Journal of Learning Analytics, vol. 6, no. 3, pp. 11–19-11–19, 2019.Google ScholarCross Ref
- X. Ochoa, S. Knight, and A. F. Wise, “Learning analytics impact: Critical conversations on relevance and social responsibility,” Journal of Learning Analytics, vol. 7, no. 3, pp. 1-5, 2020.Google ScholarCross Ref
- S. Knight, A. Gibson, and A. Shibani, “Implementing learning analytics for learning impact: Taking tools to task,” The Internet and Higher Education, vol. 45, pp. 100729, 2020.Google ScholarCross Ref
- S. Buckingham Shum, R. Ferguson, and R. Martinez-Maldonado, “Human-centred learning analytics,” Journal of Learning Analytics, vol. 6, no. 2, pp. 1-9, 2019.Google ScholarCross Ref
- A. Shibani, S. Knight, and S. B. Shum, “Educator perspectives on learning analytics in classroom practice,” The Internet and Higher Education, vol. 46, pp. 100730, 2020.Google ScholarCross Ref
- R. Bodily, and K. Verbert, “Review of research on student-facing learning analytics dashboards and educational recommender systems,” IEEE Transactions on Learning Technologies, vol. 10, no. 4, pp. 405-418, 2017.Google ScholarDigital Library
- K. Kitto, M. Lupton, K. Davis, and Z. Waters, “Designing for student-facing learning analytics,” Australasian Journal of Educational Technology, vol. 33, no. 5, pp. 152-168, 2017.Google ScholarCross Ref
- K. Verbert, E. Duval, J. Klerkx, S. Govaerts, and J. L. Santos, “Learning analytics dashboard applications,” American Behavioral Scientist, vol. 57, no. 10, pp. 1500-1509, 2013.Google ScholarCross Ref
- I. Jivet, M. Scheffel, M. Specht, and H. Drachsler, "License to evaluate: Preparing learning analytics dashboards for educational practice." pp. 31-40.Google Scholar
- P.-L. Tan, “Learner Dashboards a Double-Edged Sword? Students' Sense-Making of a Collaborative Critical Reading and Learning Analytics Environment for Fostering 21st-Century Literacies,” Journal of Learning Analytics, vol. 4, no. 1, pp. 117-140, 2017.Google ScholarCross Ref
- K. Holstein, and S. Doroudi, "Fairness and equity in learning analytics systems (FairLAK)." pp. 1-2.Google Scholar
- D. Shin, “The effects of explainability and causability on perception, trust, and acceptance: Implications for explainable AI,” International Journal of Human-Computer Studies, vol. 146, pp. 102551, 2021.Google ScholarCross Ref
- J. Knox, “Data power in education: Exploring critical awareness with the “Learning Analytics Report Card”,” Television & New Media, vol. 18, no. 8, pp. 734-752, 2017.Google ScholarCross Ref
- L. Gitelman, Raw data is an oxymoron: MIT press, 2013.Google ScholarCross Ref
- K. Kitto, S. Buckingham Shum, and A. Gibson, "Embracing imperfection in learning analytics." pp. 451-460.Google Scholar
- D. Clow, “An overview of learning analytics,” Teaching in Higher Education, vol. 18, no. 6, pp. 683-695, 2013.Google ScholarCross Ref
- A. Shibani, S. Knight, and S. Buckingham Shum, “Contextualizable Learning Analytics Design: A Generic Model, and Writing Analytics Evaluations,” in The 9th International Conference on Learning Analytics and Knowledge (LAK’19), Tempe, Arizona, 2019.Google ScholarDigital Library
- P. Goodyear, L. Carvalho, and P. Yeoman, “Activity-Centred Analysis and Design (ACAD): core purposes, distinctive qualities and current developments,” Educational Technology Research and Development, vol. 69, no. 2, pp. 445-464, 2021.Google ScholarCross Ref
- L. Lockyer, E. Heathcote, and S. Dawson, “Informing pedagogical action: Aligning learning analytics with learning design,” American Behavioral Scientist, vol. 57, no. 10, pp. 1439-1459, 2013.Google ScholarCross Ref
- L. P. Macfadyen, L. Lockyer, and B. Rienties, “Learning design and learning analytics: Snapshot 2020,” Journal of Learning Analytics, vol. 7, no. 3, pp. 6-12, 2020.Google ScholarCross Ref
- K. Gravett, “Feedback literacies as sociomaterial practice,” Critical Studies in Education, pp. 1-14, 2020.Google ScholarCross Ref
- S. Buckingham Shum, S. Knight, D. McNamara, L. Allen, D. Bektik, and S. Crossley, “Critical perspectives on writing analytics,” in Workshop at the Sixth International Conference on Learning Analytics & Knowledge, 2016, pp. 481-483.Google ScholarDigital Library
- A. Shibani, M. Liu, C. Rapp, and S. Knight, “Advances in Writing Analytics: Mapping the state of the field,” in Companion Proceedings 9th International Conference on Learning Analytics & Knowledge (LAK19), Tempe, Arizona, 2019.Google Scholar
- E. Cotos, “Automated Writing Analysis for writing pedagogy: From healthy tension to tangible prospects,” Writing and Pedagogy, vol. 6, pp. 1, 2015.Google Scholar
- S. Knight, A. Shibani, S. Abel, A. Gibson, P. Ryan, N. Sutton, R. White, C. Lucas, A. Sandor, K. Kitto, M. Liu, R. V. Mogarkar, and S. Buckingham Shum, “AcaWriter: A Learning Analytics Tool for Formative Feedback on Academic Writing,” Journal of Writing Research, 2020.Google ScholarCross Ref
- A. Shibani, S. Knight, S. Buckingham Shum, and P. Ryan, “Design and Implementation of a Pedagogic Intervention Using Writing Analytics,” in 25th International Conference on Computers in Education, New Zealand, 2017.Google Scholar
- A. Shibani, “Augmenting Pedagogic Writing Practice with Contextualizable Learning Analytics,” Connected Intelligence Centre, University of Technology Sydney, Sydney, Australia, 2019.Google Scholar
- S. Knight, A. Shibani, and S. Buckingham Shum, “Augmenting Formative Writing Assessment with Learning Analytics: A Design Abstraction Approach,” in 13th International Conference of the Learning Sciences, London, United Kingdom, 2018, pp. 1783-1790.Google Scholar
- D. Carless, and D. Boud, “The development of student feedback literacy: enabling uptake of feedback,” Assessment & Evaluation in Higher Education, vol. 43, no. 8, pp. 1315-1325, 2018.Google ScholarCross Ref
- P. Sutton, “Conceptualizing feedback literacy: knowing, being, and acting,” Innovations in Education and Teaching International, vol. 49, no. 1, pp. 31-40, 2012.Google ScholarCross Ref
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