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Technology Education

Implementing NETS for Students: Grades 9-12 By, Jessica Heflin

What is the Purpose of NETS ? N ational E ducational T echnology S tandards ,[object Object]

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Employ curriculum-specific simulations to practice critical-thinking process (1,4) ,[object Object],[object Object]

Design a Web site that meets accessibility requirements (1,5) ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]

Identify a complex issue, develop a systematic plan of investigation, and present innovative sustainable solutions (1,2,3,4) ,[object Object],[object Object],[object Object]

Illustrate and communicate original ideas and stories using digital tools and media-rich resources. (1, 2) ,[object Object]

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The emergence of learning analytics afforded for the analysis of digital traces of user interaction with technology. This analysis offers many opportunities to advance understanding and enhance learning and the environments in which learning occurs. Existing research has shown how learning analytics can provide contributions to different areas of education such as prediction of student success, uncovering learning strategies, understanding affective states, and unpacking the role social networks in learning. While these results have shown much promise, one critical challenge remains unclear – how learning analytics can help track learning progression and inform assessment especially from the perspective of the 21st century skills. This talk will explore opportunities and challenges for the integration of methods commonly used in learning analytics to analyze different digital traces with methods commonly used in assessment. The talk particularly focuses on open learning environments where analytics-based assessment is rather underexplored in contrast to assessment in specialized (intelligent tutoring) systems where the combined use of data mining and assessment has been established for some time now.

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. The emergence of learning analytics afforded for the analysis of digital traces of user interaction with technology. This analysis offers many opportunities to advance understanding and enhance learning and the environments in which learning occurs. Existing research has shown how learning analytics can provide contributions to different areas of education such as prediction of student success, uncovering learning strategies, understanding affective states, and unpacking the role social networks in learning. While these results have shown much promise, one critical challenge remains unclear – how learning analytics can help track learning progression and inform assessment especially from the perspective of the 21st century skills. This talk will explore opportunities and challenges for the integration of methods commonly used in learning analytics to analyze different digital traces with methods commonly used in assessment and psychometric research. The paper particularly focuses on open learning environments where analytics-based assessment is rather underexplored in contrast to assessment in specialized (intelligent tutoring) systems where the combined use of data mining and psychometric techniques has been established for some time now.

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