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Araos, Andrés; Damsa, Crina; Gaševic, Dragan – Journal of Computer Assisted Learning, 2023
Background: The surge of online platforms has generated interest in how specialized platforms support formal and informal learning in various disciplinary domains. Knowledge is still limited regarding how undergraduate students navigate and use platforms to learn. Objectives: This study explores computer and software engineering students' learning…
Descriptors: Computer Science Education, Computer Software, Learning Activities, Undergraduate Students
Mangaroska, Katerina; Martinez-Maldonado, Roberto; Vesin, Boban; Gaševic, Dragan – Journal of Computer Assisted Learning, 2021
Multimodal data have the potential to explore emerging learning practices that extend human cognitive capacities. A critical issue stretching in many multimodal learning analytics (MLA) systems and studies is the current focus aimed at supporting researchers to model learner behaviours, rather than directly supporting learners. Moreover, many MLA…
Descriptors: Computer Science Education, Student Attitudes, Learning Modalities, Learning Analytics
Mangaroska, Katerina; Sharma, Kshitij; Gaševic, Dragan; Giannakos, Michail – Journal of Computer Assisted Learning, 2022
Background: Problem-solving is a multidimensional and dynamic process that requires and interlinks cognitive, metacognitive, and affective dimensions of learning. However, current approaches practiced in computing education research (CER) are not sufficient to capture information beyond the basic programming process data (i.e., IDE-log data).…
Descriptors: Cognitive Processes, Psychological Patterns, Problem Solving, Programming
Ahmad Uzir, Nora'ayu; Gaševic, Dragan; Matcha, Wannisa; Jovanovic, Jelena; Pardo, Abelardo – Journal of Computer Assisted Learning, 2020
This paper aims to explore time management strategies followed by students in a flipped classroom through the analysis of trace data. Specifically, an exploratory study was conducted on the dataset collected in three consecutive offerings of an undergraduate computer engineering course (N = 1,134). Trace data about activities were initially coded…
Descriptors: Time Management, Blended Learning, Learning Analytics, Undergraduate Students
Farrow, Elaine; Moore, Johanna D.; Gaševic, Dragan – Journal of Learning Analytics, 2022
By participating in asynchronous course discussion forums, students can work together to refine their ideas and construct knowledge collaboratively. Typically, some messages simply repeat or paraphrase course content, while others bring in new material, demonstrate reasoning, integrate concepts, and develop solutions. Through the messages they…
Descriptors: Asynchronous Communication, Computer Mediated Communication, Group Discussion, Learning Analytics
Mangaroska, Katerina; Sharma, Kshitij; Gaševic, Dragan; Giannakos, Michalis – Journal of Learning Analytics, 2020
Programming is a complex learning activity that involves coordination of cognitive processes and affective states. These aspects are often considered individually in computing education research, demonstrating limited understanding of how and when students learn best. This issue confines researchers to contextualize evidence-driven outcomes when…
Descriptors: Learning Analytics, Data Collection, Instructional Design, Learning Modalities
Roll, Ido; Russell, Daniel M.; Gaševic, Dragan – International Journal of Artificial Intelligence in Education, 2018
Learning at Scale is a fast growing field that affects formal, informal, and workplace education. Highly interdisciplinary, it builds on solid foundations in the learning sciences, computer science, education, and the social sciences. We define learning at scale as the study of the technologies, pedagogies, analyses, and theories of learning and…
Descriptors: Interdisciplinary Approach, Computer Science Education, Social Sciences, Learning
Crosslin, Matt; Dellinger, Justin T.; Joksimovic, Srecko; Kovanovic, Vitomir; Gaševic, Dragan – Online Learning, 2018
Dual-layer MOOCs are an educational framework designed to create customizable modality pathways through a learning experience. The basic premise is to design two framework choices through a course: one that is instructor centered and the other that is student determined and open. Learners have the option to create their own customized pathway by…
Descriptors: Online Courses, Course Descriptions, Mixed Methods Research, Guidelines