Meaningful Assessment at Scale: Helping Instructors to Assess Online Learning.

2020 
Increased opportunities for online learning, including growth in Massive Open Online Courses (MOOCS), are changing our education environments, increasing access and flexibility in how students engage with education. However, there are still many questions regarding how we engage with students effectively in these environments, in particular through assessment. Assessment within on-line environments can vary, based on the technology available and pedagogical approach. However, forms of assessment in these environments must support additional constraints, in that they must scale to support potentially massive cohorts, minimal learner interaction, and range of learner intention. At the same time, there are unique opportunities due to the accessibility of rich learning analytics and learner data. Understanding effective assessment and assessment feedback at scale has broader implications as we cope with growing CS enrolments, and interest in technology. This working group aims to explore assessment within CS MOOCs, as a specific example of the on-line learning environment, identifying engaging and effective assessment exemplars that reflect both the constraints and opportunities of this context. The working group will (1) identify and survey existing literature on formative and summative assessment of Computer Science MOOCS, (2) clarify how assessment may be considered meaningful for students, (3) identify key features of assessment that assist an instructor in evaluating the nature and quality of learning, and (4) identifying case studies that explore both innovative and effective assessments to provide a rich experience for students and also detailed feedback to teaching staff. The outcome of this working group will be a report.
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