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El Aouifi, Houssam; El Hajji, Mohamed; Es-Saady, Youssef; Douzi, Hassan – Education and Information Technologies, 2021
This paper analyzes how learners interact with the pedagogical sequences of educational videos, and its effect on their performance. In this study, the suggested video courses are segmented on several pedagogical sequences. In fact, we're not focusing on the type of clicks made by learners, but we're concentrating on the pedagogical sequences in…
Descriptors: Video Technology, Student Behavior, Prediction, Learning Analytics
ALSaad, Fareedah; Reichel, Thomas; Zeng, Yuchen; Alawini, Abdussalam – International Educational Data Mining Society, 2021
With the emergence of MOOCs, it becomes crucial to automate the process of a course design to accommodate the diverse learning demands of students. Modeling the relationships among educational topics is a fundamental first step for automating curriculum planning and course design. In this paper, we introduce "Topic Transition Map" (TTM),…
Descriptors: Online Courses, Student Diversity, Student Needs, Course Content
Callan, Gregory L.; Cleary, Timothy J. – Metacognition and Learning, 2019
The current study used microanalytic interviews and behavioral traces to examine sequential phase relations among forethought, performance, and self-reflection processes, and to investigate the predictive influence of these processes on mathematics performance of 96 eighth grade students. Consistent with expectations, students' microanlaytic goals…
Descriptors: Prediction, Learning Processes, Metacognition, Learning Strategies
Zhou, Jianing; Bhat, Suma – Grantee Submission, 2021
Consistency of learning behaviors is known to play an important role in learners' engagement in a course and impact their learning outcomes. Despite significant advances in the area of learning analytics (LA) in measuring various self-regulated learning behaviors, using LA to measure consistency of online course engagement patterns remains largely…
Descriptors: Models, Online Courses, Learner Engagement, Learning Processes
De Nóbrega, José Renato – Teaching Statistics: An International Journal for Teachers, 2017
A strategy to facilitate understanding of spatial randomness is described, using student activities developed in sequence: looking at spatial patterns, simulating approximate spatial randomness using a grid of equally-likely squares, using binomial probabilities for approximations and predictions and then comparing with given Poisson…
Descriptors: Statistical Analysis, Sequential Approach, Pattern Recognition, Simulation
Heitmann, Christina; Deutsch, Roland – Journal of Experimental Psychology: Learning, Memory, and Cognition, 2019
Sequential effects in conflict processing (postconflict slowing and conflict adaptation) have primarily been studied in stimulus-response compatibility (SRC) tasks. Moreover, results obtained in SRC paradigms are often proposed as a model of higher-level motivational conflicts. The authors present 3 experiments suggesting that motivational…
Descriptors: Ethics, Conflict, Psychological Patterns, Cognitive Processes
Käser, Tanja; Schwartz, Daniel L. – International Educational Data Mining Society, 2019
Open-ended learning environments (OELEs) allow students to freely interact with the content and to discover important principles and concepts of the learning domain on their own. However, only some students possess the necessary skills for efficient and effective exploration. Guidance in the form of targeted interventions or feedback therefore has…
Descriptors: Educational Environment, Interaction, Cluster Grouping, Models
Mi, Fei; Faltings, Boi – International Educational Data Mining Society, 2017
Massive open online courses (MOOCs) have demonstrated growing popularity and rapid development in recent years. Discussion forums have become crucial components for students and instructors to widely exchange ideas and propagate knowledge. It is important to recommend helpful information from forums to students for the benefit of the learning…
Descriptors: Online Courses, Sequential Approach, Discussion Groups, Student Interests
Hastings, Lindsay J.; Sunderman, Hannah M. – Journal of Leadership Education, 2019
The current study examined and explained the relationship between generativity and socially responsible leadership using an explanatory sequential mixed methods design. The first, quantitative phase examined the predictive relationship between generativity and socially responsible leadership among 82 college student leaders who mentor at a…
Descriptors: Student Leadership, Social Responsibility, Mentors, Correlation
Chen, Binglin; West, Matthew; Ziles, Craig – International Educational Data Mining Society, 2018
This paper attempts to quantify the accuracy limit of "nextitem-correct" prediction by using numerical optimization to estimate the student's probability of getting each question correct given a complete sequence of item responses. This optimization is performed without an explicit parameterized model of student behavior, but with the…
Descriptors: Accuracy, Probability, Student Behavior, Test Items

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