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Prihar, Ethan; Vanacore, Kirk; Sales, Adam; Heffernan, Neil – International Educational Data Mining Society, 2023
There is a growing need to empirically evaluate the quality of online instructional interventions at scale. In response, some online learning platforms have begun to implement rapid A/B testing of instructional interventions. In these scenarios, students participate in series of randomized experiments that evaluate problem-level interventions in…
Descriptors: Electronic Learning, Intervention, Instructional Effectiveness, Data Collection
Portnoff, Lucy; Gustafson, Erin; Rollinson, Joseph; Bicknell, Klinton – International Educational Data Mining Society, 2021
Students using self-directed learning platforms, such as Duolingo, cannot be adequately assessed relying solely on responses to standard learning exercises due to a lack of control over learners' choices in how to utilize the platform: for example, how learners choose to sequence their studying and how much they choose to revisit old material. To…
Descriptors: Second Language Learning, Language Tests, Educational Technology, Electronic Learning
Hutt, Stephen; Das, Sanchari; Baker, Ryan S. – International Educational Data Mining Society, 2023
The General Data Protection Regulation (GDPR) in the European Union contains directions on how user data may be collected, stored, and when it must be deleted. As similar legislation is developed around the globe, there is the potential for repercussions across multiple fields of research, including educational data mining (EDM). Over the past two…
Descriptors: Data Analysis, Decision Making, Data Collection, Foreign Countries
Marwan, Samiha; Shi, Yang; Menezes, Ian; Chi, Min; Barnes, Tiffany; Price, Thomas W. – International Educational Data Mining Society, 2021
Feedback on how students progress through completing subgoals can improve students' learning and motivation in programming. Detecting subgoal completion is a challenging task, and most learning environments do so either with "expert-authored" models or with "data-driven" models. Both models have advantages that are…
Descriptors: Expertise, Models, Feedback (Response), Identification
Cechák, Jaroslav; Pelánek, Radek – International Educational Data Mining Society, 2021
Measuring similarity of educational items has several applications in the development of adaptive learning systems, and previous research has already proposed a wide range of similarity measures. In this work, we provide an experimental evaluation of selected similarity measures using a large dataset. The used items are alternate-choice questions…
Descriptors: Measurement, Proximity, Grammar, English (Second Language)
Sturludóttir, Erla Guðrún; Arnardóttir, Eydís; Hjálmtýsson, Gísli; Óskarsdóttir, María – International Educational Data Mining Society, 2021
Gaining insight into course choices holds significant value for universities, especially those who aim for flexibility in their programs and wish to adapt quickly to changing demands of the job market. However, little emphasis has been put on utilizing the large amount of educational data to understand these course choices. Here, we use network…
Descriptors: Course Selection (Students), Undergraduate Students, Engineering Education, Business Administration Education
Mitrovic, Antonija, Ed.; Bosch, Nigel, Ed. – International Educational Data Mining Society, 2022
For this 15th iteration of the International Conference on Educational Data Mining (EDM 2022), the conference was held in Durham, England, with an online hybrid format for virtual participation as well. EDM is organized under the auspices of the International Educational Data Mining Society. The theme of this year's conference is Inclusion,…
Descriptors: Information Retrieval, Data Analysis, Feedback (Response), Inclusion
Zhang, Mo; Guo, Hongwen; Liu, Xiang – International Educational Data Mining Society, 2021
We present an empirical study on the use of keystroke analytics to capture and understand how writers manage their time and make inferences on how they allocate their cognitive resources during essay writing. The results suggest three distinct longitudinal patterns of writing process that describe how writers approach an essay task in a writing…
Descriptors: Keyboarding (Data Entry), Learning Analytics, Data Collection, Cognitive Processes