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Contextualization, Authenticity, and the Problem Description Effect
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Ellie Lovellette; Dennis J. Bouvier; John Matta – ACM Transactions on Computing Education, 2024
In recent years, computing education researchers have investigated the impact of problem context on students' learning and programming performance. This work continues the investigation motivated, in part, by cognitive load theory and educational research in computer science and other disciplines. The results of this study could help inform…
Descriptors: Computer Science Education, Student Evaluation, Context Effect, Problem Solving
The Impact of Attribute Noise on the Automated Estimation of Collaboration Quality Using Multimodal Learning Analytics in Authentic Classrooms
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Pankaj Chejara; Luis P. Prieto; Yannis Dimitriadis; Maria Jesus Rodriguez-Triana; Adolfo Ruiz-Calleja; Reet Kasepalu; Shashi Kant Shankar – Journal of Learning Analytics, 2024
Multimodal learning analytics (MMLA) research has shown the feasibility of building automated models of collaboration quality using artificial intelligence (AI) techniques (e.g., supervised machine learning (ML)), thus enabling the development of monitoring and guiding tools for computer-supported collaborative learning (CSCL). However, the…
Descriptors: Learning Analytics, Attribution Theory, Acoustics, Artificial Intelligence
An Operations Research-Based Teaching Unit for Grade 11: The ROAR Experience, Part II
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Gabriella Colajanni; Alessandro Gobbi; Marinella Picchi; Alice Raffaele; Eugenia Taranto – INFORMS Transactions on Education, 2024
In this paper, we continue describing the project and the experimentation of "Ricerca Operativa Applicazioni Reali" (ROAR; in English, Real Applications of Operations Research), a three-year project for higher secondary schools, introduced. ROAR is composed of three teaching units, addressed to Grades 10, 11, and 12, respectively, having…
Descriptors: Foreign Countries, Grade 11, Operations Research, High School Students
FATE in MMLA: A Student-Centred Exploration of Fairness, Accountability, Transparency, and Ethics in Multimodal Learning Analytics
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Yueqiao Jin; Vanessa Echeverria; Lixiang Yan; Linxuan Zhao; Riordan Alfredo; Yi-Shan Tsai; Dragan Gasevic; Roberto Martinez-Maldonado – Journal of Learning Analytics, 2024
Multimodal learning analytics (MMLA) integrates novel sensing technologies and artificial intelligence algorithms, providing opportunities to enhance student reflection during complex, collaborative learning experiences. Although recent advancements in MMLA have shown its capability to generate insights into diverse learning behaviours across…
Descriptors: Learning Analytics, Accountability, Ethics, Artificial Intelligence
An Operations Research-Based Teaching Unit for Grade 10: The ROAR Experience, Part I
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Gabriella Colajanni; Alessandro Gobbi; Marinella Picchi; Alice Raffaele; Eugenia Taranto – INFORMS Transactions on Education, 2023
We introduce "Ricerca Operativa Applicazioni Reali" (ROAR; in English, "Real Applications of Operations Research"), a three-year project for higher secondary schools. Its main aim is to improve students' interest, motivation, and skills related to Science, Technology, Engineering, and Mathematics disciplines by integrating…
Descriptors: Operations Research, High School Students, Grade 10, Foreign Countries