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Husni Mubarok; Chi-Jen Lin; Gwo-Jen Hwang – Interactive Learning Environments, 2024
In language learning, it is important to foster students' computational thinking and improve their skills of building arguments and dialectical structure, teamwork, and decision accuracy. This is especially so in English language courses which aim to promote students' cultural learning interest, creative thinking, and oral presentation.…
Descriptors: English (Second Language), Computer Simulation, Second Language Learning, Cooperative Learning
Wuwen Zhang; Yurong Guan; Zhihua Hu – Education and Information Technologies, 2024
In the context of our rapidly digitizing society, computational thinking stands out as an essential attribute for cultivating aptitude and expertise. Through the prism of computational thinking, learners are more adeptly positioned to dissect and navigate real-world challenges, poising them effectively to meet the exigencies of future societal…
Descriptors: Active Learning, Student Projects, Computation, Thinking Skills
Jamie Colwell; Amy Hutchison; Kristie Gutierrez; Jeff Offutt; Anya Evmenova – Computer Science Education, 2024
Background & Context: This research focused on an online professional development (PD), the Inclusive Computer Science Model of PD, to support integrating computer science and computational thinking for all learners into K-5 literacy instruction. Objective: This research was conducted to understand elementary teachers' perceptions of the PD.…
Descriptors: Elementary School Teachers, Teaching Experience, Electronic Learning, Faculty Development
Jui-Hung Chang; Chi-Jane Wang; Hua-Xu Zhong; Hsiu-Chen Weng; Yu-Kai Zhou; Hoe-Yuan Ong; Chin-Feng Lai – Educational Technology Research and Development, 2024
Amidst the rapid advancement in the application of artificial intelligence learning, questions regarding the evaluation of students' learning status and how students without relevant learning foundation on this subject can be trained to familiarize themselves in the field of artificial intelligence are important research topics. This study…
Descriptors: Artificial Intelligence, Technological Advancement, Student Evaluation, Models
Sarah Gerard; Emily Relkin; Claire Christensen; Naomi Hupert; Erika Gaylor – Society for Research on Educational Effectiveness, 2024
Background: Computational thinking (CT) is a way of thinking that helps children solve problems and complete tasks in more organized ways, using computer science skills. Prior research indicates that promoting CT skills in young children can support the acquisition of general problem solving (PS), executive function (EF), and social emotional…
Descriptors: Computation, Thinking Skills, Video Games, Computer Games
Niknam, Mehdi; Thulasiraman, Parimala – Education and Information Technologies, 2020
The educational community has been interested in personalized learning systems that can adapt itself while providing learning support to different learners to overcome the weakness of 'one size fits all' approaches in technology-enabled learning systems. In this paper, one known problem in adaptive learning systems called curriculum sequencing is…
Descriptors: Educational Technology, Electronic Learning, Learning Theories, Computation
Martínez, Sergio; Rueda, Maria; Arcos, Antonio; Martínez, Helena – Sociological Methods & Research, 2020
This article discusses the estimation of a population proportion, using the auxiliary information available, which is incorporated into the estimation procedure by a probit model fit. Three probit regression estimators are considered, using model-based and model-assisted approaches. The theoretical properties of the proposed estimators are derived…
Descriptors: Computation, Regression (Statistics), Statistical Analysis, Population Groups
Koster, Jeremy; Leckie, George; Aven, Brandy – Field Methods, 2020
The multilevel social relations model (SRM) is a commonly used statistical method for the analysis of social networks. In this article and accompanying supplemental materials, we demonstrate the estimation and interpretation of the SRM using Stat-JR software. Multiple software templates permit the analysis of different response types, including…
Descriptors: Statistical Analysis, Computer Software, Hierarchical Linear Modeling, Social Networks
Köhler, Carmen; Robitzsch, Alexander; Hartig, Johannes – Journal of Educational and Behavioral Statistics, 2020
Testing whether items fit the assumptions of an item response theory model is an important step in evaluating a test. In the literature, numerous item fit statistics exist, many of which show severe limitations. The current study investigates the root mean squared deviation (RMSD) item fit statistic, which is used for evaluating item fit in…
Descriptors: Test Items, Goodness of Fit, Statistics, Bias
Chen, Yalin; Orr, Alicia; Campbell, Jamie I. D. – Journal of Experimental Psychology: Learning, Memory, and Cognition, 2020
This research pursued a fine-grained analysis of the acquisition of a procedural skill. In two experiments (n = 29 and n = 27), adults practiced 12 alphabet arithmetic problems (e.g., C + 3 = C D E F) in two sessions with 20 practice blocks in each. If learning reflected speed up of a counting algorithm, response time (RT) speed up should be…
Descriptors: Learning Processes, Alphabets, Arithmetic, Computation
Askew, Mike; Venkat, Hamsa – ZDM: The International Journal on Mathematics Education, 2020
The cardinal and ordinal aspects of number have been widely written about as key constructs that need to be brought together in children's understanding in order for them to appreciate the idea of numerosity. In this paper, we discuss similarities and differences in the ways in which understandings not only of ordinality, cardinality but also…
Descriptors: Foreign Countries, Elementary School Students, Grade 1, Mathematical Concepts
Luthra, Sahil; You, Heejo; Rueckl, Jay G.; Magnuson, James S. – Cognitive Science, 2020
Visual word recognition is facilitated by the presence of "orthographic neighbors" that mismatch the target word by a single letter substitution. However, researchers typically do not consider "where" neighbors mismatch the target. In light of evidence that some letter positions are more informative than others, we investigate…
Descriptors: Visual Stimuli, Word Recognition, Orthographic Symbols, Alphabets
Lyford, Alex; Czekanski, Michael – Teaching Statistics: An International Journal for Teachers, 2020
Students are typically introduced to probability through calculating simple events like flipping a coin. While these calculations can be done by hand, more complex probabilistic events, both in class and in the real world, require the use of computers. In this paper, we introduce a new tool--an R shiny web app and associated CRAN package based on…
Descriptors: Probability, Games, Simulation, Mathematics Instruction
Melhuish, Kathleen; Ellis, Brittney; Hicks, Michael D. – Educational Studies in Mathematics, 2020
Binary operations are one of the fundamental structures underlying our number and algebraic systems. Yet, researchers have often left their role implicit as they model student understanding of abstract structures. In this paper, we directly analyze students' perceptions of the general binary operation via a two-phase study consisting of task-based…
Descriptors: Mathematics Instruction, Mathematical Concepts, Concept Formation, Computation
Lee, Hea-Jin; Boyadzhiev, Irina – International Electronic Journal of Mathematics Education, 2020
This study investigated understanding of and misconceptions with fractions in college students enrolled in a remedial mathematics course. Data were collected from 22 college students for one semester. The analysis of 41 fraction problems revealed that participants' common misconceptions were associated with a lack of understanding of basic…
Descriptors: College Students, College Mathematics, Mathematics Skills, Misconceptions

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