Idiographic learning analytics : A single student (N=1) approach using psychological networks

• Recent findings in the field of learning analytics have brought to our attention that conclusions drawn from cross-sectional group-level data may not capture the dynamic processes that unfold within each individual learner. In this light, idiographic methods have started to gain grounds in many fields as a possible solution to examine students' behavior at the individual level by using several data points from each learner to create person-specific insights. In this study, we introduce such novel methods to the learning analytics field by exploring the possible potentials that one can gain from zooming in on the fine-grained dynamics of a single student. Specifically, we make use of Gaussian Graphical Models -an emerging trend in network science- to analyze a single student's dispositions and devise insights specific to him/her. The results of our study revealed that the student under examination may be in need to learn better self-regulation techniques regarding reflection and planning. 

Ämnesord

NATURVETENSKAP  -- Data- och informationsvetenskap -- Datavetenskap (hsv//swe)

NATURAL SCIENCES  -- Computer and Information Sciences -- Computer Sciences (hsv//eng)

SAMHÄLLSVETENSKAP  -- Utbildningsvetenskap -- Pedagogik (hsv//swe)

SOCIAL SCIENCES  -- Educational Sciences -- Pedagogy (hsv//eng)

Nyckelord

Graphical Gaussian Models

Idiographic learning analytics

Network science

Psychological networks

Students

Dynamic process

Emerging trends

Fine grained

Gaussian graphical models

Individual levels

Novel methods

Self regulation

Students' behaviors

Learning systems

Technology and Learning

Publikations- och innehållstyp

ref (ämneskategori)

kon (ämneskategori)