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Esteban Villalobos; Isabel Hilliger; Carlos Gonzalez; Sergio Celis; Mar Pérez-Sanagustín; Julien Broisin – Journal of Learning Analytics, 2024
Researchers in learning analytics have created indicators with learners' trace data as a proxy for studying learner behaviour in a college course. Student Approaches to Learning (SAL) is one of the theories used to explain these behaviours, distinguishing between deep, surface, and organized study. In Latin America, researchers have demonstrated…
Descriptors: Learning Analytics, Academic Achievement, Role Theory, Learning Processes
Yun Tang; Zhengfan Li; Guoyi Wang; Xiangen Hu – Interactive Learning Environments, 2023
To better understand the self-regulated learning process in online learning environments, this research applied a data mining method, the two-layer hidden Markov model (TL-HMM), to explore the patterns of learning activities. We analyzed 25,818 entries of behavior log data from an intelligent tutoring system. Results indicated that students with…
Descriptors: Electronic Learning, Learning Activities, Self Management, Intelligent Tutoring Systems
Camilla Svens-Liavåg; Johan Korhonen; Sol-Britt Arnolds-Granlund – Scandinavian Journal of Educational Research, 2024
The aim of this study was to examine what kind of school performance and behaviour profiles could be identified among students in the final grade of basic education in the Swedish speaking parts of Finland (N = 1149, grade 9), how these differed in temperament and how temperament could explain profile differences in first language (L1, Swedish)…
Descriptors: Foreign Countries, Adolescents, Grade 9, Academic Achievement
Jing Liu; Megan Kuhfeld; Monica Lee – Annenberg Institute for School Reform at Brown University, 2023
Noncognitive constructs such as self-efficacy, social awareness, and academic engagement are widely acknowledged as critical components of human capital, but systematic data collection on such skills in school systems is complicated by conceptual ambiguities, measurement challenges and resource constraints. This study addresses this issue by…
Descriptors: Student Behavior, Predictor Variables, Predictive Validity, Academic Achievement
Li, Yue; Jiang, Qiang; Xiong, Weiyan; Zhao, Wei – Education and Information Technologies, 2023
One of the recognized ways to enhance teaching and learning is having insights into the behavior patterns of students. Studies that explore behavior patterns in online self-directed learning (OSDL) are scant though. In addition, the focus is lacking on how high-achieving (HA) students' behavior patterns affect the academic performance of…
Descriptors: Student Behavior, Behavior Patterns, Electronic Learning, Online Courses
Balti, Rihab; Hedhili, Aroua; Chaari, Wided Lejouad; Abed, Mourad – Education and Information Technologies, 2023
Since the COVID pandemic, universities propose online education to ensure learning continuity. However, the insufficient preparation led to a major drop in the learner's performance and his/her dissatisfaction with the learning experience. This may be due to several reasons, including the insensitivity of the virtual learning environment to the…
Descriptors: Cognitive Style, Pandemics, COVID-19, Distance Education
Chen, Changsheng; Meng, Xiangzeng – International Journal of Distance Education Technologies, 2021
As a supplement to face-to-face teaching, small private online courses (SPOCs) have become increasingly popular in higher education. Nevertheless, there is a lack of research on behavioral patterns in the university SPOC. This empirical study investigates the behavioral patterns of 306 undergraduate students taking a degree course partially taught…
Descriptors: Student Behavior, Behavior Patterns, Outcomes of Education, Online Courses
Hsu, Ting-Chia; Chang, Ching; Liang, Yi-Sian – IEEE Transactions on Learning Technologies, 2023
The study explores the effects of an interdisciplinary learning approach on developing students' English learning (EL) and computational thinking (CT) through two different game-based learning approaches. A quasi-experiment is conducted to evaluate the effectiveness of this approach in terms of enhancing students' CT knowledge and their EL…
Descriptors: Elementary School Students, Grade 3, Interdisciplinary Approach, Computation
Çebi, Ayça; Araújo, Rafael D.; Brusilovsky, Peter – Journal of Research on Technology in Education, 2023
Online learning systems allow learners to freely access learning contents and record their interactions throughout their engagement with the content. By using data mining techniques on the student log data of those systems, it is possible to examine learning behavior and reveal navigation patterns through learning contents. This study was aimed at…
Descriptors: Individual Characteristics, Electronic Learning, Student Behavior, Learning Management Systems
Jeynes, William H. – Education and Urban Society, 2022
The meta-analysis, that included 75 studies, examined the relationship between illegal drug consumption, on the one hand, and student academic and behavioral outcomes, on the other, for the middle school to college grade levels. The meta-analysis first (research question #1) addressed whether there is a statistically significant relationship…
Descriptors: Middle School Students, High School Students, College Students, Drug Use
van den Beemt, Antoine; Buys, Joos; van der Aalst, Wil – International Review of Research in Open and Distributed Learning, 2018
The increasing use of digital systems to support learning leads to a growth in data regarding both learning processes and related contexts. Learning Analytics offers critical insights from these data, through an innovative combination of tools and techniques. In this paper, we explore students' activities in a MOOC from the perspective of personal…
Descriptors: Online Courses, Student Behavior, Behavior Patterns, Academic Achievement
Özerk, Gül – International Electronic Journal of Elementary Education, 2020
Academic boredom is a complex and underestimated problem in schools in many countries. The research on this phenomenon is mostly from Germany and Northern America. During the last two-three decades several studies have highlighted some aspects of academic boredom and its relationship to motivation and school-based learning behavior and outcomes.…
Descriptors: Learner Engagement, Student Motivation, Goal Orientation, Academic Achievement
Wu, Wen-Chi; Lin, I.-Ting; Chen Hsieh, Jun – Asia-Pacific Education Researcher, 2023
The knowledge of English idioms is essential for advanced English learning and application, particularly for English-as-a-foreign-language (EFL) learners. While studies have shown the benefits of mobile-assisted language learning (MALL) to facilitate English learning, few studies have examined the factors that may influence MALL in light of…
Descriptors: Foreign Countries, English, Language Patterns, Learning Modalities
Vandell, Deborah Lowe; Simpkins, Sandra D.; Pierce, Kim M.; Brown, B. Bradford; Bolt, Dan; Reisner, Elizabeth – Applied Developmental Science, 2022
Patterns of afterschool activities were studied in low-income, ethnically diverse children (n = 1796, M age = 8.7 yrs). Cluster analyses indicated four reliable clusters: (a) regular participation in a high-quality afterschool program, (b) regular participation at the afterschool program combined with other extracurricular activities, (c)…
Descriptors: After School Programs, Extracurricular Activities, Low Income Students, Student Participation
Kuo, Wei-Chen; Hsu, Ting-Chia – Asia-Pacific Education Researcher, 2020
This study utilized unplugged computational thinking learning material named Robot City as the instructional material. The board game corresponds to structural programming, including sequential structure, conditional structure, repetitive structure, and the modeling concept of calling a procedure in programming languages. According to the…
Descriptors: Thinking Skills, Computation, Educational Games, Instructional Materials