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Di Sun; Gang Cheng; Heng Luo – Interactive Learning Environments, 2024
Recently, researchers have proposed to leverage technology-supported data (log files) to investigate temporal and sequential patterns of interaction behaviors in learning processes. There are two major challenges to be addressed: clarifying the positioning of interaction levels and identifying the evolution of the interaction action patterns in…
Descriptors: Foreign Countries, Undergraduate Students, Computer Science, MOOCs
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Mengning Mu; Man Yuan – Interactive Learning Environments, 2024
The necessity for students to clarify their own cognitive structure and the amount of their knowledge mastery for self-reflection is often ignored in building the student model in the adaptive model, which makes the construction of the cognitive structure pointless. Simultaneously, knowledge forgetting causes students' knowledge level to fall…
Descriptors: Individualized Instruction, Cognitive Processes, Graphs, Cognitive Structures
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Hassan Kilavo; Tabu S. Kondo; Feruzi Hassan – Interactive Learning Environments, 2024
Today computing is intricate in all aspects of our lives, beginning with communications and education to banking, information security, health, shopping, and social media. Development of the computing is proportional to the development of software which is becoming a serious part of all daily lives. This paper, therefore, assessed the impact of…
Descriptors: Foreign Countries, Computer Science Education, Elementary School Students, Outcomes of Education
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O. S. Adewale; O. C. Agbonifo; E. O. Ibam; A. I. Makinde; O. K. Boyinbode; B. A. Ojokoh; O. Olabode; M. S. Omirin; S. O. Olatunji – Interactive Learning Environments, 2024
With the advent of technological advancement in learning, such as context-awareness, ubiquity and personalisation, various innovations in teaching and learning have led to improved learning. This research paper aims to develop a system that supports personalised learning through adaptive content, adaptive learning path and context awareness to…
Descriptors: Cognitive Style, Individualized Instruction, Learning Processes, Preferences
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Ünal Çakiroglu; Seval Bilgi – Interactive Learning Environments, 2024
The aim of this explanatory study is to identify the causes of intrinsic cognitive load in programming process. For this purpose, a method based on two dimensions; programming knowledge types (syntactic, semantic, and strategic) and programming constructs was proposed. The proposed method was tested with high school students enrolled in Computer…
Descriptors: Cognitive Processes, Difficulty Level, Programming, Interaction
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Tyler S. Love – Interactive Learning Environments, 2024
Providing greater access to computer science (CS) education for K-12 students in the United States (U.S.) has increased interest in integrating CS concepts within authentic science, technology, engineering, and mathematics (STEM) contexts. Physical computing is one method that has demonstrated promising results in other countries (e.g. England)…
Descriptors: Middle School Students, Student Attitudes, Computer Science Education, STEM Education
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YungYu Zhuang; Yu-Hsuan Lin; Mahesh Liyanawatta; Andito Haryo Saputro; Yuniati Dwi Utami; Jen-Hang Wang – Interactive Learning Environments, 2024
Computer programming is essential nowadays but still challenging to learn due to its invisible thinking. Current programming environments are mostly designed for operating on computers directly to learn concrete programming, but this approach lacks the support for clarifying learners' thinking processes. On the other hand, using paper and pens…
Descriptors: Educational Environment, Thinking Skills, Programming, Computer Science Education
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Ding-Chau Wang; Yong-Ming Huang – Interactive Learning Environments, 2024
Tiny and affordable computers (e.g. Raspberry Pi and Arduino) have been widely applied to technology-enhanced hands-on learning (THL). However, little scholarly attention has been devoted to the key factors behind students' performance in THL contexts. Therefore, this study not only helped the participants learn computer science through THL, but…
Descriptors: Handheld Devices, Self Efficacy, Educational Technology, Computer Science Education
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Jiahong Su; Kai Guo; Xinyu Chen; Samuel Kai Wah Chu – Interactive Learning Environments, 2024
The teaching of artificial intelligence (AI) has increasingly become a topic of investigation among educational researchers. Studies of AI education have predominantly focused on the university level; less attention has been paid to teaching AI in K-12 classrooms. This study synthesised empirical studies on K-12 AI education, with the aims of…
Descriptors: Artificial Intelligence, Computer Science Education, Elementary Secondary Education, Teaching Methods
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Yuan-Chen Liu; Tzu-Hua Huang; Chien-Chia Huang – Interactive Learning Environments, 2024
In this study, an interactive programming learning environment was built with two types of error prompt functions: 1) the key prompt and 2) step-by-step prompt. A quasi-experimental study was conducted for five weeks, in which 75 sixth grade students from disadvantaged learning environments in Taipei, Taiwan, were divided into three groups: 1) the…
Descriptors: Programming, Computer Science Education, Cues, Grade 6
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Gang Yang; Dan Zheng; Ji-Huan Chen; Qun-Fang Zeng; Yun-Fang Tu; Xiao-Li Zheng – Interactive Learning Environments, 2024
The game-based learning approach to developing students' computational thinking (CT) current has received attention from researchers. However, the compatibility between games and instruction is often insufficient to accommodate the entertaining and educational nature of the curriculum entirely, and the benefits of game-based learning could be…
Descriptors: Role Playing, Educational Games, Mental Computation, Learner Engagement
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Shruti Priya; Shubhankar Bhadra; Sridhar Chimalakonda; Akhila Sri Manasa Venigalla – Interactive Learning Environments, 2024
Owing to the predominant role of Machine Learning(ML) across domains, it is being introduced at multiple levels of education, including K-12. Researchers have leveraged games, augmented reality and other ways to make learning ML concepts interesting. However, most of the existing games to teach ML concepts either focus on use-cases and…
Descriptors: Artificial Intelligence, Secondary School Students, Video Games, Visual Aids
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Qian Fu; Wenjing Tang; Yafeng Zheng; Haotian Ma; Tianlong Zhong – Interactive Learning Environments, 2024
In this study, a predictive model is constructed to analyze learners' performance in programming tasks using data of programming behavioral events and behavioral sequences. First, this study identifies behavioral events from log data and applies lag sequence analysis to extract behavioral sequences that reflect learners' programming strategies.…
Descriptors: Predictor Variables, Psychological Patterns, Programming, Self Management
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Na Li; Erick Purwanto; Xiaojun Zhang; Feng Cao; Kok Hoe Wong; Xiangru Chen – Interactive Learning Environments, 2024
To address the problem of poor efficacy in hybrid learning in higher education, this study conducted a mix-method explanatory case study with structural equation modelling to examine a new construct, "perceived pedagogical value" (PPV), and its relationship with the core constructs of the Unified Theory of Acceptance and Use of…
Descriptors: Educational Benefits, Interaction, Blended Learning, College Students
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Ramazan Yilmaz – Interactive Learning Environments, 2024
This research, students' technology acceptance, KSB, community of inquiry (CoI), and social interaction space situations were examined in collaborative learning where Zoom was used as a CSCL tool in computer programming courses, and the structural relationships between these variables were revealed. The research was carried out on 162 university…
Descriptors: Cooperative Learning, Technology Uses in Education, Technological Literacy, Student Attitudes
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