Joseph Dauer
Biographic Data
| ID | 6553247 |
|---|---|
| NAME | Joseph Dauer |
| GIVEN NAMES | Joseph |
| FAMILY NAME | Dauer |
| SIGNATURE | DAUER J |
| AFFILIATIONS | University of Nebraska–Lincoln |
| ORCID | 0000-0002-8971-0441 |
| VERIFIED | Yes |
| TOTAL WORKS | 4 |
| TOTAL CITATIONS | 0 |
| AUTHOR COUNT | 4 |
| EDITOR COUNT | 0 |
| FIRST PUBLICATION YEAR | 2021 |
| LATEST PUBLICATION YEAR | 2024 |
| H-INDEX | 0 |
Individual variation in undergraduate student metacognitive monitoring and error detection during biology model evaluation
Introduction Models are a primary mode of science communication and preparing university students to evaluate models will allow students to better construct models and predict phenomena. Model evaluation relies on students’ subject-specific knowledge, perception of model characteristics, and confidence in their knowledge structures. Methods Fifty first-year college biology students evaluated models of concepts from varying biology subject areas w…
Development of the Quantitative Modelling Observation Protocol (QMOP) for undergraduate biology courses
Educational reform priorities such as emphasis on quantitative modelling (QM) have positioned undergraduate biology instructors as designers of QM experiences to engage students in authentic science practices that support the development of data-driven and evidence-based reasoning. Yet, little is known about how biology instructors adapt to the pedagogical movement towards incorporating QM opportunities for students in the courses they teach. Thi…
Revision as an essential step in modeling to support predicting, observing, and explaining cellular respiration system dynamics
Comprehensive understanding of complex biological systems necessitates the use of computational models because they facilitate visualisation and interrogation of system dynamics and data-driven analysis. Computational model-based (CMB) activities have demonstrated effectiveness in improving students’ understanding and their ability to use and reason with models. To maximise the effectiveness of computational modelling, this study examined an impr…
Assessing quantitative modelling practices, metamodelling, and capability confidence of biology undergraduate students
Quantitative modelling plays an important role as biology increasingly deals with big data sets, relies on modelling to understand system dynamics, makes predictions about impacts of changes, and revises our understanding of system interactions. An assessment of quantitative modelling in biology was administered to students (n = 612) in undergraduate biology courses at two universities to provide a picture of student ability in quantitative reaso…
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Assessing quantitative modelling practices, metamodelling, and capability confidence of biology undergraduate students
Quantitative modelling plays an important role as biology increasingly deals with big data sets, relies on modelling to understand system dynamics, makes predictions about impacts of changes, and revises our understanding of system interactions. An assessment of quantitative modelling in biology was administered to students (n = 612) in undergraduate biology courses at two universities to provide a picture of student ability in quantitative reaso…
Revision as an essential step in modeling to support predicting, observing, and explaining cellular respiration system dynamics
Comprehensive understanding of complex biological systems necessitates the use of computational models because they facilitate visualisation and interrogation of system dynamics and data-driven analysis. Computational model-based (CMB) activities have demonstrated effectiveness in improving students’ understanding and their ability to use and reason with models. To maximise the effectiveness of computational modelling, this study examined an impr…
Individual variation in undergraduate student metacognitive monitoring and error detection during biology model evaluation
Introduction Models are a primary mode of science communication and preparing university students to evaluate models will allow students to better construct models and predict phenomena. Model evaluation relies on students’ subject-specific knowledge, perception of model characteristics, and confidence in their knowledge structures. Methods Fifty first-year college biology students evaluated models of concepts from varying biology subject areas w…
Development of the Quantitative Modelling Observation Protocol (QMOP) for undergraduate biology courses
Educational reform priorities such as emphasis on quantitative modelling (QM) have positioned undergraduate biology instructors as designers of QM experiences to engage students in authentic science practices that support the development of data-driven and evidence-based reasoning. Yet, little is known about how biology instructors adapt to the pedagogical movement towards incorporating QM opportunities for students in the courses they teach. Thi…
Computer Science (4 works) · Mathematics education (4 works) · Psychology (4 works) · Science Education and Pedagogy (4 works) · Artificial Intelligence (2 works) · Cognition (2 works) · Genetics, Bioinformatics, and Biomedical Research (2 works) · Innovative Teaching and Learning Methods (2 works) · Machine learning (2 works) · Science education (2 works)