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Computer science is often integrated within early childhood education (ECE) through the use of educational robots. This requires adequate preparation of ECE teachers to program and debug, which can be done with scaffolding. In this paper, we use a QUANT + qual mixed method approach incorporating lag sequential analysis, ICAP framework coding, sentiment analysis, and supplementary qualitative analysis. Students tended to engage more with tasks in the revision and evaluation phases than in the exploration phase, and became less dependent on scaffolding prompts and more competent in debugging, as debugging task complexity increased. This study addresses a key gap in the scaffolding literature in that it examined learners' interactions with scaffolding for evidence of decreased reliance on scaffolding. [ABSTRACT FROM AUTHOR]

This paper presents a game-design workshop built around a digital art installation featuring video games displayed over a real-world skyscraper to stimulate students' interest in computer science and a study testing its short-term effects on improving middle school students' computational thinking (CT) skills and attitudes towards computing. Following a STEAM approach, the workshop aimed to engage participants in age-appropriate activities that focus on CT skills through the lens of creating their own game. A web-based game design interface that allows students to code and play games as simulated on a skyscraper was developed to support the workshop's core activities. The web environment also featured step-by-step tutorials and fully functional games to promote the accessibility of the learning materials for a diverse body of students and educators around the globe. The results of the study indicated that the workshop helped students improve their CT skills and differentially influence their attitudes towards computing. In particular, the workshop experience led students from underserved community districts to lower their attitude ratings, whereas the reverse pattern was observed for students from more affluent districts. The workshop reportedly informed students' perception of computing as a profession and their appreciation of the analytical effort required for developing functional games. Qualitative analysis of artifact-based interviews indicated that students could begin to make abstractions and devise algorithms by associating variables through conditional statements while solving problems related to game development. Interview analysis also revealed that students took pride in the effort that they made during the workshop. [ABSTRACT FROM AUTHOR]

This paper examined the nuances of the background process of design and development and follow up classroom implementation of computer-based models for high school chemistry. More specifically, the study examined the knowledge contributions of an interdisciplinary team of experts; points of tensions, negotiations and non-negotiable aspects of model design; and the evolutionary trajectory of technological artefacts as they are readied for classroom implementation. A Discourse-in-use methodological approach examined planning sessions involved in the design and development of models and a case study of classroom implementation in two high school chemistry classrooms were conducted. The data included transcripts of planning sessions, classroom observations and teacher and student interviews. Design and development sessions reflected five major themes: (i) the nature of models: function, goals and limitations of models (ii) the role of students, background knowledge, and goals for student learning (ii) pedagogical decisions of the modeling process (iv) models and assessment and (v) the role of implementation. In comparison to the educator group, the scientist/programmer knowledge contributions dominated the form that technologies eventually assumed. Surely, implementation exposed teacher and student challenges with sub micro NetLogo representations; this finding reinforced the tensions and non-negotiable aspects of design that were involved in ensuring accurate representations. Models were configured to accommodate what was scientifically and technically reproducible within the constraints of context. However, these visual representations were not always commensurable with chemistry expectations at the high school level. These findings have implications for pedagogical decisions aligned with implementation, content understanding and assessment; and the sustainability of computer-based models in precollege science classrooms. [ABSTRACT FROM AUTHOR]

With a growing number of ScratchJr usage, over 19 million users worldwide, we examined the use in the United States of the free ScratchJr programming language, explicitly designed for young children ages 5–7, to learn how to code. Our objective was to explore children's usage of the ScratchJr tablet app at home and school settings. We analyzed usage data from Google Analytics in 1.5 years, comparing Scratchsr usage in the two different settings. Our dataset comprised a total of 4,352,802 coding sessions, generated by a daily average of 2525 home users and 9969 school users. The results suggested that, although children in both settings on average spent an equal duration with ScratchJr, children in home settings spent more time exploring advanced coding blocks and the paint editor compared to children at school. Further, children at school tended to use similar types of coding blocks across several days. In contrast, children at home were more likely to use a diversity of block categories and difficulty levels. The implications of this research are, first, that usage patterns may help us understand how children across settings learn to program differently. Second, based on these findings, it may be essential for parents at home and educators at school to consider using different approaches and strategies. [ABSTRACT FROM AUTHOR]

This systematic review of research on adaptive learning used a strategic search process to synthesize research on adaptive learning based on publication trends, instructional context, research methodology components, research focus, adaptive strategies, and technologies. A total of 61 articles on adaptive learning were analyzed to describe the current state of research and identify gaps in the literature. Descriptive characteristics were recorded, including publication patterns, instructional context, and research methodology components. The count of adaptive learning articles published fluctuated across the decade and peaked in 2015. During this time, the largest concentration of adaptive learning articles appeared in Computers and Education. The majority of the studies occurred in higher education in Taiwan and the United States, with the highest concentration in the computer science discipline. The research focus, adaptive strategies, and adaptive technologies used in these studies were also reviewed. The research was aligned with various instructional design phases, with more studies examining design and development, and implementation and evaluation. For examining adaptive strategies, the authors examined both adaptive sources based on learner model and adaptive targets based on content and instructional model. Learning style was the most observed learner characteristic, while adaptive feedback and adaptive navigation were the most investigated adaptive targets. This study has implications for adaptive learning designers and future researchers regarding the gaps in adaptive learning research. Future studies might focus on the increasing availability and capacities of adaptive learning as a learning technology to assist individual learning and personalized growth. [ABSTRACT FROM AUTHOR]