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Ting-Ting Wu; Edi Sarwono; Yueh-Min Huang – Journal of Computer Assisted Learning, 2025
Background: Virtual laboratories are used to supplement or even replace physical laboratories in engineering education. Although these virtual laboratories allow students to learn foundational experimental skills, they do not provide the learners with the chance to develop higher-order thinking skills (HOTS). Computational thinking (CT) is an…
Descriptors: Computation, Thinking Skills, Computer Simulation, Laboratories
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Heping Xie; Zongkui Zhou – Journal of Computer Assisted Learning, 2024
Background: Drawing is generally regarded as a promising learning strategy and has been explored in the touchscreen setting with different drawing modes. Although both a finger and a digital pencil can help individuals complete drawing activities effortlessly on touchscreen devices, there is no guarantee that they show the same effect on learning,…
Descriptors: Computer System Design, Visual Aids, Eye Movements, Freehand Drawing
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Chunqi Li; Lishi Liang; Luke K. Fryer; Alex Shum – Journal of Computer Assisted Learning, 2024
Background: Leaderboards are among the most popular gamification elements in education. Some studies have implemented leaderboards and reported their individual effects on students' learning. Despite the emergence of relevant empirical studies, most of the existing reviews have only investigated the holistic impact of gamification. No previous…
Descriptors: Higher Education, Gamification, Evidence Based Practice, Learning Motivation
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Sayginer, Senol; Tüzün, Hakan – Journal of Computer Assisted Learning, 2023
Background: Studies on the effectiveness of block-based environments continue to produce inconsistent results. A strong reason for this is that most studies compare environments that are not equivalent to each other or to the level of learners. Moreover, studies that present evidence of the effectiveness of block-based environments by comparing…
Descriptors: Programming, Academic Achievement, Logical Thinking, Thinking Skills
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Lars de Vreugd; Anouschka van Leeuwen; Marieke van der Schaaf – Journal of Computer Assisted Learning, 2025
Background: University students need to self-regulate but are sometimes incapable of doing so. Learning Analytics Dashboards (LADs) can support students' appraisal of study behaviour, from which goals can be set and performed. However, it is unclear how goal-setting and self-motivation within self-regulated learning elicits behaviour when using an…
Descriptors: Learning Analytics, Educational Technology, Goal Orientation, Learning Motivation
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Esnaashari, Shadi; Gardner, Lesley A.; Arthanari, Tiru S.; Rehm, Michael – Journal of Computer Assisted Learning, 2023
Background: It is vital to understand students' Self-Regulatory Learning (SRL) processes, especially in Blended Learning (BL), when students need to be more autonomous in their learning process. In studying SRL, most researchers have followed a variable-oriented approach. Moreover, little has been known about the unfolding process of students' SRL…
Descriptors: Metacognition, Student Attitudes, Learning Strategies, Questionnaires
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Ankora, Carlos; Bolatimi, Stephen Oladagba; Bensah, Lily; Mahama, Francois; Kuadey, Noble Arden; Adu, Adolph Sedem Yaw; Adjei, Laurene – Journal of Computer Assisted Learning, 2023
Background: The degree to which Computer Science (CS) and Information Communication Technology (ICT) students are motivated to learn greatly impacts their study habits, academic achievement in school and ultimately their job prospects. In recent times, skills in programming languages have become vital in searching for employment. Objective: This…
Descriptors: College Students, Student Motivation, Course Selection (Students), Programming Languages
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Liping Jiang; Menglei Lv; Mengmeng Cheng; Xia Chen; Changhong Peng – Journal of Computer Assisted Learning, 2024
Background: The introduction of Small Private Online Courses (SPOCs) in English as a Foreign Language (EFL) instruction at Higher Vocational Colleges (HVCs) signifies a shift in education. Understanding the factors that affect deep learning in this SPOC context is crucial for improving educational outcomes. Objectives: By employing grounded…
Descriptors: Higher Education, Vocational Education, College Students, Private Education
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Liujie Xu; Xuefei Zou; Yuxue Hou – Journal of Computer Assisted Learning, 2024
Background: Data literacy (DL) is vital for teachers, as it enables them to build on data and improve teaching and learning. Therefore, developing DL among pre-service teachers is critical. Objectives: The purpose of this study is threefold: to evaluate whether a feedback visualisation of peer assessment-based teaching approach (FVPA-based…
Descriptors: Statistics Education, Comparative Analysis, Preservice Teachers, Teacher Education Programs
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Truzoli, Roberto; Viganò, Caterina; Galmozzi, Paolo Gabriele; Reed, Phil – Journal of Computer Assisted Learning, 2020
The current study explored the relationship between problematic internet use (PIU) and motivation to learn, and examined psychological and social factors mediating this relationship. Two hundred and eighty-five students in an Italian University were recruited for the current study. There was a negative relationship between PIU and motivation to…
Descriptors: Internet, Learning Motivation, College Students, Psychological Patterns
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Rahman, Md. H Asibur; Uddin, Mohammad Shahab; Dey, Anamika – Journal of Computer Assisted Learning, 2021
The purpose of this paper is to investigate the mediating role of online learning motivation (OLM) in the COVID-19 pandemic situation in Bangladesh by observing and comparing direct lectures (DL), instructor-learner interaction (ILI), learner-learner interaction (LLI), and internet self-efficacy (ISE) as predictors of OLM and online learning…
Descriptors: Online Courses, Learning Motivation, COVID-19, Pandemics
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Fu, En; Gao, Qiufeng; Wei, Chuqian; Chen, Qianyi; Liu, Yijun – Journal of Computer Assisted Learning, 2021
Smartphone use in learning settings is a common behaviour amongst college students. Building on the theory of consumerism, self-efficacy and addictive behaviours, the current study developed a three-component conceptual framework to understand college students' smartphone use in organizational as well as self-directed learning settings. One…
Descriptors: Foreign Countries, College Students, Handheld Devices, Telecommunications
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Shao, Kaiqi; Kutuk, Gulsah; Fryer, Luke K.; Nicholson, Laura J.; Guo, Jidong – Journal of Computer Assisted Learning, 2023
Background: Considerable evidence suggests that students' achievement emotions are important contributors to their learning and success online. It is, therefore, essential to understand and support students' emotional experiences to enhance online education, especially under the COVID-19 context. However, to date, very few studies have…
Descriptors: Student Attitudes, Undergraduate Students, English (Second Language), Second Language Learning
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Gao, Fei; Zhao, Na; Li, Xiumei – Journal of Computer Assisted Learning, 2020
This study was conducted to examine how a collaborative social annotation tool can be used to support collaborative learning in translation instruction for EFL students. Participants were 100 undergraduate students who were English majors in a southeast university in China. An experiment with crossover design was carried out to examine the…
Descriptors: Translation, Student Motivation, Student Attitudes, Cooperative Learning
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Thai, Ngoc Thuy Thi; De Wever, Bram; Valcke, Martin – Journal of Computer Assisted Learning, 2020
This study compares four learning environments: face-to-face learning (F2F), fully e-learning (EL), blended learning (BL), and flipped classroom (FC) with respect to students' learning performance. Moreover, this present research studies changes in perceived flexibility, intrinsic motivation, self-efficacy beliefs of students, and the interaction…
Descriptors: Blended Learning, Teaching Methods, Comparative Analysis, Self Efficacy
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