Learning Analytics for the Formative Assessment of New Media Skills

Recent theories of education have shifted learning environments towards student-centred education. Also, the advancement of technology and the need for skilled individuals in different areas have led to the introduction of new media skills. Along with new pedagogies and content, these changes require new forms of assessment. However, assessment as the core of learning has not been modified as much as other educational aspects. Hence, much attention is required to develop assessment methods based on current educational requirements. To address this gap, we have implemented two data-driven systematic literature reviews to recognize the existing state of the field in the current literature. Chapter four of this thesis focus on a literature review of automatic assessment, named learning analytics. This chapter investigates the topics and challenges in developing new learning analytics tools. Chapter five studies all assessment types, including traditional and automatic forms, in computational thinking education. Computational thinking education, which refers to the teaching of problem-solving skills, is one of the new media skills introduced in the 21st century. The findings from these two literature reviews categorize the assessment methods and identify the key topics in the literature of learning analytics and computational thinking assessment. Studying the identified topics, their relations, and related studies, we pinpoint the challenges, requirements, and opportunities of using automatic assessment in education. The findings from these studies can be used as a guideline for future studies aiming to enhance assessment methods in education. Also, the literature review strategy in this thesis can be utilized by other researchers to develop systematic data-driven literature reviews in future studies