A one stop shop? Perspectives on the value of adaptive learning technologies in K-12 education

COMPUTERS AND EDUCATION OPEN(2023)

引用 0|浏览1
暂无评分
摘要
This study explored the value of Adaptive Learning Technologies (ALTs) in K-12 education by examining the advantages and challenges these tools create for teaching and learning from the perspectives of stakeholders involved in the use (Teachers), implementation (Teacher Support professionals), and development (EdTech professionals) of ALTs. We conducted qualitative thematic analysis on 25 stakeholder interviews using the Teacher Response Model as a guide for examining stakeholders' perceptions of the advantages and challenges of ALTs. Analysis resulted in three overarching concepts (i.e., learning management, student agency and engagement, and implementation challenges), under which themes regarding stakeholder perspectives on the advantages and challenges of ALTs could be organized and contrasted with one another. Learning management themes suggest that stakeholders perceive features such as real-time student data and tailored learning content as creating value for teachers by supporting efficiency in their learning management, however that value is impacted by stakeholders' concerns with ALT grading and data collection processes. Student agency and engagement themes highlight how certain user interaction features can create value or challenges for learners depending on whether the features were designed with students' developmental and competence needs in mind. Finally, the implementation challenges themes suggest that for ALTs to create value in K-12 settings, stakeholders need better alignment around their ALT implementation goals and expectations. We leverage these data to make recommendations for future research and development so stakeholders can maximize the affordances of ALTs for K-12 students and teachers.
更多
查看译文
关键词
Distance education and online learning,Improving classroom teaching,Elementary education,Secondary education,Teaching/Learning strategies
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要