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Ying-Lien Lin; Wei-Tsong Wang; Zhi-Lun Lai – Education and Information Technologies, 2025
Although some studies have examined the effects of self-regulated learning (SRL) strategies on learning effectiveness, inconsistent results have been reported. Additionally, studies that adopt the perspective of SRL to evaluate the effect of metacognitive skills on students' actual learning effectiveness in digital game-based learning (DGBL)…
Descriptors: Prior Learning, Metacognition, Game Based Learning, Learning Strategies
Lokkila, Erno; Christopoulos, Athanasios; Laakso, Mikko-Jussi – Informatics in Education, 2023
Prior programming knowledge of students has a major impact on introductory programming courses. Those with prior experience often seem to breeze through the course. Those without prior experience see others breeze through the course and disengage from the material or drop out. The purpose of this study is to demonstrate that novice student…
Descriptors: Prior Learning, Programming, Computer Science Education, Markov Processes
Umapathy, Karthikeyan; Ritzhaupt, Albert D.; Xu, Zhen – Journal of Educational Computing Research, 2020
The purpose of this research was to examine college students' conceptions of learning computer science and approaches to learning computer science and to examine the relationships among these two important constructs and possible moderating factors. Student data (N = 193) were collected using the conceptions of learning computer science and the…
Descriptors: Computer Science Education, Prior Learning, Learning Motivation, Programming
Razieh Fathi – ProQuest LLC, 2021
This dissertation describes an experiment to investigate how learners with different levels of background in computer science learn core concepts of computer science, in particular, algorithms. We designed a study to focus on cognitive task analysis for eliciting the empirical mental elements of learning two graph algorithms. Cognitive workload…
Descriptors: Undergraduate Students, Computer Science Education, Algorithms, Cognitive Development
Christopoulos, Athanasios; Conrad, Marc; Shukla, Mitul – Journal of Educational Technology Systems, 2018
This research links learner engagement with interactions when Hybrid Virtual Learning models are used. Various aspects have been considered, such as learners' prior experiences related to virtual worlds, their preconceptions regarding their use as a learning tool, and the impact that instructional designers' choices have on enhancing the…
Descriptors: Educational Games, Blended Learning, Computer Simulation, Learner Engagement
Akar, Sacide Guzin Mazman; Altun, Arif – Contemporary Educational Technology, 2017
The purpose of this study is to investigate and conceptualize the ranks of importance of social cognitive variables on university students' computer programming performances. Spatial ability, working memory, self-efficacy, gender, prior knowledge and the universities students attend were taken as variables to be analyzed. The study has been…
Descriptors: Individual Differences, Learning Processes, Programming, Self Efficacy
Tegos, Stergios; Demetriadis, Stavros; Papadopoulos, Pantelis M.; Weinberger, Armin – International Journal of Computer-Supported Collaborative Learning, 2016
Conversational agents that draw on the framework of academically productive talk (APT) have been lately shown to be effective in helping learners sustain productive forms of peer dialogue in diverse learning settings. Yet, literature suggests that more research is required on how learners respond to and benefit from such flexible agents in order…
Descriptors: Interpersonal Communication, Computer Mediated Communication, Academic Discourse, Peer Relationship
Robins, Anthony – Computer Science Education, 2010
Compared to other subjects, the typical introductory programming (CS1) course has higher than usual rates of both failing and high grades, creating a characteristic bimodal grade distribution. In this article, I explore two possible explanations. The conventional explanation has been that learners naturally fall into populations of programmers and…
Descriptors: Programming, Learning Processes, Grading, Simulation
Simon, Beth; Bouvier, Dennis; Chen, Tzu-Yi; Lewandowski, Gary; McCartney, Robert; Sanders, Kate – Computer Science Education, 2008
We report on responses to a series of four questions designed to identify pre-existing abilities related to debugging and troubleshooting experiences of novice students before they begin programming instruction. The focus of these questions include general troubleshooting, bug location, exploring unfamiliar environments, and describing students'…
Descriptors: Troubleshooting, Teaching Methods, Computer Science Education, Programming
PDF pending restorationBott, Ross A. – 1979
An analysis and model of the cognitive processes underlying complex learning situations are presented. A theory is proposed that attempts to specify particular internal knowledge structures generated and modified during instruction, and to use them to explain specific difficulties that the learner experiences and also the overall progress being…
Descriptors: Analogy, Computer Science Education, Concept Formation, Difficulty Level
Miyake, Naomi; Norman, Donald A. – 1978
This study involved the manipulation of question-asking in a learning task. The hypothesis that learners should ask the most questions when their knowledge was well-matched to the level of presentation was tested, using two levels of background knowledge and two levels of difficulty of material to be learned. The more simple instructional…
Descriptors: Academic Ability, Classification, Computer Science Education, Difficulty Level
International Association for Development of the Information Society, 2012
The IADIS CELDA 2012 Conference intention was to address the main issues concerned with evolving learning processes and supporting pedagogies and applications in the digital age. There had been advances in both cognitive psychology and computing that have affected the educational arena. The convergence of these two disciplines is increasing at a…
Descriptors: Academic Achievement, Academic Persistence, Academic Support Services, Access to Computers

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