Digital Assessment in the Artificial Intelligence Age
Title:
Digital Assessment in the Artificial Intelligence Age
Wordcount:
3000 words (excluding abstract and references)
Abstract:
Technology is increasingly being adopted to support the presentation and administration of assessment activities. This has led to the development of digital tools and techniques that aim to provide technology-enhanced methods for assessing students. In this regard, digital assessment is often seen as providing a more efficient way of conducting assessment activities, by automating various aspects of the assessment process. However, digital technologies have the potential to achieve much more than simply provide a digital version of standardised assessment tasks that can be completed offline. In particular, the use of emerging technologies, such as Artificial Intelligence (AI) for assessment purposes, is becoming an area of educational theory and practice, that is of great interest to assessment developers and researchers. This is due to the ability of AI-based assessment systems to provide assessment activities that are more responsive to the specific needs of individual learners, and which can be automatically adapted in real-time to the level of understanding demonstrated by the learner.
This paper examines the defining characteristics of AI in light of the constructive alignment and interaction that exists between theories of learning and the different functions of assessment. On analysing the respective literature in the fields of assessment and AI, we provide the key underpinnings of AI for digital assessment purposes and argue that assessment activities that are informed by AI, have the potential to address key limitations normally associated with traditional assessment approaches, and thus support more effective assessment practices. We also discuss the implications of using AI for assessment, and identify a number of key challenges that need to be addressed in order to realise the potential of this technology. Finally, we suggest future avenues for research, as we envisage that the application of AI in education will result in an enhanced assessment experience for both students and educators.
NOTE: You can use parts of the Abstract in the main text
Outline:
Introduction (250 words)
Theories of Learning and Assessment (800 words)
- Theories of Learning:
– Behaviourism
– Cognitivism
– Constructivism
- Assessment:
– Define assessment
– Functions of assessment: summative and formative
– Define summative assessment and provide examples
– Define formative assessment and provide examples
In this section, you need to critically evaluate the summative and formative dimensions of assessment in the light of the theories of learning discussed above, especially with regard to Constructivism.
Digital Assessment (400 words)
– Define digital assessment
– Provide examples of digital assessment (techniques and tools)
– Critically evaluate the benefits and challenges (for example, one-size-fits-all) of digital assessments
From Abstract: In this regard, digital assessment is often seen as providing a more efficient way of conducting assessment activities, by automating various aspects of the assessment process. However, digital technologies have the potential to achieve much more than simply provide a digital version of standardised assessment tasks that can be completed offline.
Artificial Intelligence for Digital Assessment (1200 words)
– Define Artificial Intelligence (AI)
– Discuss the key characteristics of AI, these being ‘autonomous’ and ‘adaptive’ (hence personalised assessment, self-regulation, differentiated teaching and learning, individualised feedforward (which is forward-looking information to improve teaching and learning – like feedback but looking at the future), real-time feedforward, etc.) and how these relate to the theories of learning and functions of assessment described above.
– In particular, critically analyse how these two characteristics, these being autonomous and adaptive, address the challenges of traditional and digital assessment discussed above.
– Discuss the implications of AI for digitial assessment
– Discuss the challenges of using AI digital assessment
Conclusion (350 words)
– How does AI enhance digital assessment practices?
– What are the limitations of AI for digital assessment practices?
– Future directions of AI for assessment
