Influences on the Development of Economic Knowledge over the First Academic Year

et al. 2020

Sensors

Self Cite

Learning to solve graph tasks is one of the key prerequisites of acquiring domain-specific knowledge in most study domains. Analyses of graph understanding often use eye-tracking and focus on analyzing how much time students spend gazing at particular areas of a graph—Areas of Interest (AOIs). To gain a deeper insight into students’ task-solving process, we argue that the gaze shifts between students’ fixations on different AOIs (so-termed transitions) also need to be included in holistic analyses of graph understanding that consider the importance of transitions for the task-solving process. Thus, we introduced Epistemic Network Analysis (ENA) as a novel approach to analyze eye-tracking data of 23 university students who solved eight multiple-choice graph tasks in physics and economics. ENA is a method for quantifying, visualizing, and interpreting network data allowing a weighted analysis of the gaze patterns of both correct and incorrect graph task solvers considering the interrelations between fixations and transitions. After an analysis of the differences in the number of fixations and the number of single transitions between correct and incorrect solvers, we conducted an ENA for each task. We demonstrate that an isolated analysis of fixations and transitions provides only a limited insight into graph solving behavior. In contrast, ENA identifies differences between the gaze patterns of students who solved the graph tasks correctly and incorrectly across the multiple graph tasks. For instance, incorrect solvers shifted their gaze from the graph to the x-axis and from the question to the graph comparatively more often than correct solvers. The results indicate that incorrect solvers often have problems transferring textual information into graphical information and rely more on partly irrelevant parts of a graph. Finally, we discuss how the findings can be used to design experimental studies and for innovative instructional procedures in higher education.

Section: Participantsmentioning

confidence: 70%

Epistemic Network Analyses of Economics Students’ Graph Understanding: An Eye-Tracking Study

Brückner

Schneider

et al. 2020

Sensors

Self Cite

“…This can partly be explained by the fact that both study domains are known for being mass study courses. Previous studies reveal only a low and often non-significant role of large-scale (introductory) lectures (Schlax et al 2020).…”

Section: Discussionmentioning

confidence: 93%

Entry Assessment of Student Learning Preconditions in Higher Education: Implications for the Transition from Secondary to Tertiary Education in Germany

Schlax

2020

European Review

Self Cite

The acquisition of domain-specific knowledge and interdisciplinary skills such as critical thinking is increasingly gaining significance as key learning outcomes in higher education that are crucial for all professionals and engaged citizens and that enable lifelong learning. Despite this socio-political consensus, up until the last decade there have only been a few evidence-based insights into the competencies of higher education students. Therefore, the Germany-wide research program Modelling and Measuring Competencies in Higher Education (KoKoHs) was established in 2011 by the Federal Ministry of Education and Research. In the 85 projects, theoretical-conceptual competence models and corresponding assessments were developed for selected large study domains (e.g. economics) to reliably measure the students’ competencies in different phases of higher education (entering, undergraduate, graduate). More than 100 technology-based assessments of both discipline-specific competencies and generic skills were validated across Germany at over 350 universities with over 75,000 students. This article presents findings from the Germany-wide entry diagnostics in the one KoKoHs project (WiWiKom II) with beginning students in business, economic and social sciences that provide evidence-based insights into students’ learning preconditions and their impact on domain-specific knowledge acquisition in bachelor’s degree courses. The results lead to far-reaching practical implications for successful transitions between secondary and tertiary education, including recommendations for the development of mechanisms to support access to tertiary education and to prevent high dropout rates.

“…The learning opportunities offered in the respective degree programs mostly led to increases in competence during studies (Münchow et al 2020). Remarkably, initial individual differences in entry-level competencies rarely decreased during the course of studies (Kraitzek et al 2020;Schlax et al 2020).…”

Section: How Can the Development Of Students' Competencies In He Be Described And Scaled?mentioning

confidence: 98%

“…Pedagogical competencies seemed to be linked more to a learning effect and generic competencies more to students' personal characteristics. In DK, no significant correlations were found in the aggregated data set, but in the individual projects focusing on competence development, effects of gender (Schlax et al 2020), migration background, language skills (Hammer et al 2015), previous education, and length of study (and, thus, also learning effects) on competence levels became evident (e.g., Kuhn et al 2020;Vogelsang et al 2020).…”

Section: Which Personal and Institutional Factors Can Significantly Explain The Acquisition Of Students' Competencies?mentioning

confidence: 99%

Mapping Competency Acquisition in Higher Education and Its Influences: A Meta-Study

Toepper

Braunheim

2021

JoSPoE

Self Cite

In the 10-year research program "Modelling and Measuring Competencies in Higher Education (KoKoHs)" that ran from 2011 until 2020, more than 100 theoretically sound models and corresponding tests were developed to analyze the level and development of students’ competencies. Using these newly developed assessments, generic and domain-specific competencies of more than 75,000 students at more than 350 German universities in numerous disciplines (e.g., economics, teacher education) were measured in 39 interdisciplinary collaborative KoKoHs projects. Method: In these measurements, a nationally and internationally unique database was created that contains information on the level, acquisition, and development of competencies, as well as corresponding personal and contextual influences, among students at different stages throughout their studies. A comprehensive meta-analysis of the students’ competencies as well as of the central factors influencing the acquisition of competencies in higher education had not been conducted so far. The existing KoKoHs data had only been analyzed in isolation within the individual KoKoHs projects until then. Accordingly, the obtained results related only to the individual project level. To address this research deficit, the meta-study presented in this paper conducted a research synthesis, i.e., a systematic and structured meta-analysis of the KoKoHs database. Results: The meta-study describes the acquisition of competencies in higher education across domains and provides empirical evidence on generalizable versus specific influencing factors and, thus, evidence-based practical knowledge for higher education practice and policy.