Structural Assessment of Knowledge as, of, and for Learning

Trumpower, David L.; Vanapalli, Arun

doi:10.1007/978-3-319-17727-4_23-1

Cited by 5 publications

(2 citation statements)

References 43 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Pre- and post-test MMA was assessed using a structural knowledge assessment method based on the relatedness ratings of relevant domain concepts (e.g., Kraiger et al, 1995; Wouters et al, 2011). In the field of education, structural knowledge assessment has previously been used to assess mental models in a variety of topics (for an overview, see Trumpower and Vanapalli, 2016). Additionally, structural assessment has been applied in the context of multimedia learning to investigate mental model development in domains such as medical skills training (van der Spek et al, 2010, 2011; Wouters et al, 2011) and financial education (Riemer and Schrader, 2016a).…”

Section: Methodsmentioning

confidence: 99%

Mental Model Development in Multimedia Learning: Interrelated Effects of Emotions and Self-Monitoring

Riemer¹,

Schrader²

2019

Front. Psychol.

View full text Add to dashboard Cite

Learners’ emotions and metacognitive self-monitoring play a crucial role in mental model development, particularly in the context of multimedia learning. However, learning-centered emotions and self-monitoring have been investigated largely without accounting for their dynamic interrelations. In this study, the effects of both learner-state variables on mental model development were investigated, by modeling their interrelations over time during a multimedia learning episode. For this, 108 undergraduate students ( M age = 22.79, SD age = 3.42) were engaged in a multimedia learning environment to learn practical money skills. Learning-centered emotions of enjoyment, boredom, and frustration were repeatedly collected using self-reports. Learners’ self-monitoring was assessed using behavioral data in terms of time spent on accessing specific information in the multimedia environment. Mental model development was operationalized by assessing learners’ mental model accuracy (MMA) in pre- and post-tests, by using assessments of structural knowledge. Regarding the dynamic interrelations, panel models with the repeated measures revealed positive direct and indirect paths from earlier stages of self-monitoring to later stages of enjoyment. Conversely, negative direct and indirect paths emerged from earlier stages of boredom and frustration to later stages of self-monitoring. Regarding the effects of all variables on mental model development, a path model analysis with aggregated values revealed that enjoyment was unrelated to post-test MMA, whereas boredom negatively predicted post-test MMA. Additionally, frustration negatively predicted self-monitoring, which positively predicted post-test MMA. Finally, pre-test MMA was a negative predictor of boredom and positively predicted post-test MMA. The results demonstrate that the dynamic interrelations between different learning-centered emotions and self-monitoring can diverge in multimedia learning. In addition, this study provides insights into the joint effects and the relative importance of emotions and self-monitoring for mental model development in multimedia learning.

show abstract

Section: Methodsmentioning

confidence: 99%

Mental Model Development in Multimedia Learning: Interrelated Effects of Emotions and Self-Monitoring

Riemer¹,

Schrader²

2019

Front. Psychol.

View full text Add to dashboard Cite

show abstract

“…This proves that the instrument has good specificity. The intended specificity is the instrument's ability to distinguish the specificity of each factor based on its correlation value (Trumpower et al, 2010). The results of Cronbach's alpha analysis in Table 3 reveal that the reliability value ranges from 0.74 to 0.85.…”

Section: Discussionmentioning

confidence: 99%

Validating Student’s Green Character Instrument Using Factor and Rasch Model

Sukri¹,

Arief²,

Purwanti³

et al. 2022

EUROPEAN J ED RES

View full text Add to dashboard Cite

<p style="text-align: justify;">Many researchers have separately developed instruments to measure environmental characteristics such as attitudes, values, and knowledge. However, there is no instrument used to measure all these aspects in one comprehensive instrument. This study is meant to develop and validate a green character instrument which reveals student behavior and awareness of the environment. The instrument consists of 40 statement items consisting of 5 aspects, namely private pro-environmental behavior, public pro-environmental behavior, environmental knowledge, environmental values, and environmental attitudes. It was implemented on 1,398 students from 15 universities in Indonesia. The instrument content validation was analyzed by three experts using content validity index (CVI). The construct validity was analyzed using exploratory factor analysis, confirmatory factor analysis, and RASCH analysis. The content validity results obtained CVI scores ranging between 0.8 and 0.9 with a good category, while item reliability was in a fairly good category with a high level of separation index. Construct validation resulted in 34 items (4 items were eliminated after Exploratory and Confirmatory Factor Analysis, and 2 items were eliminated after RASCH analysis) spread over five constructs, namely environmental behavior, environmental knowledge, environmental values, environmental attitudes, and environmental habits. The resulting instrument has a good level of item difficulty, with a well understood response set which can be understood easily by respondents, and without bias. Therefore, it can be used to measure the students’ green character on both male and female.</p>

show abstract

Reducing the Gap Between the Conceptual Models of Students and Experts Using Graph-Based Adaptive Instructional Systems

Giabbanelli

Tawfik

2020

Lecture Notes in Computer Science

View full text Add to dashboard Cite

Structural Assessment of Knowledge as, of, and for Learning

Cited by 5 publications

References 43 publications

Mental Model Development in Multimedia Learning: Interrelated Effects of Emotions and Self-Monitoring

Mental Model Development in Multimedia Learning: Interrelated Effects of Emotions and Self-Monitoring

Validating Student’s Green Character Instrument Using Factor and Rasch Model

Reducing the Gap Between the Conceptual Models of Students and Experts Using Graph-Based Adaptive Instructional Systems

Contact Info

Product

Resources

About