Measuring Professional Competence Using Computer-Generated Log Data

Research output: Contribution to book/conference proceedings/anthology/reportChapter in book/anthology/reportContributed

Contributors

Abstract

One of the benefits of computer-based assessments lies in the automatic generation of log data. Such behavioural process data provide a time-stamped documentation of students’ interactions with the assessment system (e.g., mouse clicks). This chapter explores the usefulness of computer-generated log data for the measurement of professional competence and their potential for the research on professional learning and development. Based on a selection of studies, we illustrate how interindividual differences in task completion processes can be analysed with the help of log data, e.g. to identify the use of certain problem-solving strategies, or to reveal subgroups of students with efficiency barriers. We further present our own research, where we applied a theory on the diagnostic process (Abele, Vocat Learn 11(1):133–159, 2018) in order to assess diagnostic strategies (Abele and von Davier, CDMs in vocational education: assessment and usage of diagnostic problem-solving strategies in car mechatronics. In: von Davier M, Lee YS (eds) Handbook of diagnostic classification models. Springer International Publishing, pp 461–488. https://doi.org/10.1007/978-3-030-05584-4_22, 2019) in the domain of car mechatronics using log data. A profound understanding of interindividual process differences may supplement a merely product-oriented competence measurement and pave the way for a more process-oriented approach. Challenges concerning the assessment, analysis and interpretation of log data will be discussed.

Details

Original languageGerman
Title of host publicationMethods for Researching Professional Learning and Development
EditorsMichael Goller, Eva Kyndt, Susanna Paloniemi, Crina Damşa
PublisherSpringer Link
Pages165-186
Number of pages22
Volume33
Publication statusPublished - 2022
Peer-reviewedNo

External IDs

Scopus 85137587858
ORCID /0000-0002-3689-8428/work/142235929

Keywords