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Durak, Hatice Yildiz – Journal of Educational Computing Research, 2020
Learning the basic concepts of programming and its foundations is considered as a challenging task for students to figure out. It is a challenging process for lecturers to learn these concepts, as well. The current literature on programming training abounds with the examples of a wide range of methods employed. Within this context, one of the…
Descriptors: Educational Technology, Technology Uses in Education, Programming, Teaching Methods
Šaric-Grgic, Ines; Grubišic, Ani; Šeric, Ljiljana; Robinson, Timothy J. – International Journal of Distance Education Technologies, 2020
The idea of clustering students according to their online learning behavior has the potential of providing more adaptive scaffolding by the intelligent tutoring system itself or by a human teacher. With the aim of identifying student groups who would benefit from the same intervention in AC-ware Tutor, this research examined online learning…
Descriptors: Learning Analytics, Intelligent Tutoring Systems, Grouping (Instructional Purposes), Undergraduate Students
Lui, Debora; Kafai, Yasmin; Litts, Breanne; Walker, Justice; Widman, Sari – Computer Science Education, 2020
Background and Context: Physical computing involves complex negotiations of multiple, on and off-screen tasks, which calls for research on how to best structure collaborative work to ensure equitable learning. Objective: We focus on how pairs self-organized their multi-domain tasks in physical computing, and how their social interactions supported…
Descriptors: Cooperative Learning, High School Students, Computer Science Education, Programming
Yao, Mengfan; Sahebi, Shaghayegh; Behnagh, Reza Feyzi – International Educational Data Mining Society, 2020
Student procrastination, as the voluntary delay of intended work despite expecting to be worse off for the delay, is an important factor with potentially negative consequences in student well-being and learning. In online educational settings such as Massive Open Online Courses (MOOCs), the effect of procrastination is considered to be even more…
Descriptors: Large Group Instruction, Online Courses, Student Behavior, Study Habits
Mao, Ye; Marwan, Samiha; Price, Thomas W.; Barnes, Tiffany; Chi, Min – International Educational Data Mining Society, 2020
Modeling student learning processes is highly complex since it is influenced by many factors such as motivation and learning habits. The high volume of features and tools provided by computer-based learning environments confounds the task of tracking student knowledge even further. Deep Learning models such as Long-Short Term Memory (LSTMs) and…
Descriptors: Time, Models, Artificial Intelligence, Bayesian Statistics
Dawar, Deepak – Information Systems Education Journal, 2022
Learning computer programming is a challenging task for most beginners. Demotivation and learned helplessness are pretty common. A novel instructional technique that leverages the value-expectancy motivational model of student learning was conceptualized by the author to counter the lack of motivation in the introductory class. The result was a…
Descriptors: Teaching Methods, Introductory Courses, Computer Science Education, Assignments
Kaniadakis, Antonios; Padumadasa, Eranjan Udayanga – Journal of Information Systems Education, 2022
Students enrolling to university holding vocational qualifications to study Computer Science and Electronic Engineering struggle to adapt to the requirements of academic life. As a result, they show higher dropout rates and perform less well than the sector-adjusted average. Following a socio-cultural approach, we present a practice-based…
Descriptors: Electronic Learning, College Students, Online Courses, Professional Identity
Ma, Yingbo; Katuka, Gloria Ashiya; Celepkolu, Mehmet; Boyer, Kristy Elizabeth – International Educational Data Mining Society, 2022
Collaborative learning is a complex process during which two or more learners exchange opinions, construct shared knowledge, and solve problems together. While engaging in this interactive process, learners' satisfaction toward their partners plays a crucial role in defining the success of the collaboration. If intelligent systems could predict…
Descriptors: Middle School Students, Cooperative Learning, Prediction, Peer Relationship
Riese, Emma; Bälter, Olle – ACM Transactions on Computing Education, 2022
Assessment plays an important role in education and can both guide and motivate learning. Assessment can, however, be carried out with different aims: providing the students with feedback that supports the learning (formative assessment) and judging to which degree the students have fulfilled the intended learning outcomes (summative assessment).…
Descriptors: Introductory Courses, Programming, Computer Science Education, Learning Motivation
Babik, Dmytro – Journal of Information Systems Education, 2022
Agile system development approaches, such as Scrum, have become popular with a wide spectrum of organizations from start-ups to government agencies. Recruiters and executives have been seeking graduates with Scrum competency beyond cursory familiarity. CIS programs responded with a variety of activities and exercises to address this need. This…
Descriptors: Teaching Methods, Computer Science Education, Computer Software, Undergraduate Students
The Discourse-Based Interview on Twitch: Methods for Studying the Tacit Knowledge of Game Developers
Shivener, Rich; Da Silva, Jessica Oliveira; Rahman, Anika – Composition Forum, 2022
In this essay, we argue that Twitch is an incredible platform for cultivating discourse-based interviews (DBIs) and has yet to be addressed in DBI research involving digital tools. To demonstrate that argument, we detail the methods behind collaborative research project between two undergraduates and a faculty studying game developers on the…
Descriptors: Discourse Analysis, Interviews, Computer Software, Barriers
Knight, G.; Powell, N.; Woods, G. – European Journal of Engineering Education, 2022
Computer Science (CS) degrees have some of the poorest continuation rates across HE. This study describes an intervention within a diverse CS student cohort to identify students who may be at risk of mathematical academic failure and the success of student mentor-led workshops in enhancing these students' mathematical ability. Diagnostic screening…
Descriptors: Undergraduate Students, Computer Science Education, Learner Engagement, Attendance
Bakke, Christine; Sakai, Rena – Journal of Information Technology Education: Innovations in Practice, 2022
Aim/Purpose: This research aims to describe layering of career-like experiences over existing curriculum to improve perceived educational value. Background: Feedback from students and regional businesses showed a clear need to increase student's exposure to career-like software development projects. The initial goal was to develop an…
Descriptors: Computer Software, Best Practices, Feedback (Response), Computer Science Education
Finke, Sabrina; Kemény, Ferenc; Sommer, Markus; Krnjic, Vesna; Arendasy, Martin; Slany, Wolfgang; Landerl, Karin – Computer Science Education, 2022
Background: Key to optimizing Computational Thinking (CT) instruction is a precise understanding of the underlying cognitive skills. Román-González et al. (2017) reported unique contributions of spatial abilities and reasoning, whereas arithmetic was not significantly related to CT. Disentangling the influence of spatial and numerical skills on CT…
Descriptors: Spatial Ability, Cognitive Ability, Abstract Reasoning, Arithmetic
Er, Erkan – Online Submission, 2022
Time management is an important self-regulation strategy that can improve student learning and lead to higher performance. Students who can manage their time effectively are more likely to exhibit consistent engagement in learning activities and to complete course assignments in a timely manner. Well planning of the study time is an essential part…
Descriptors: Programming, Time Management, Computer Science Education, Integrated Learning Systems

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