Assessing quantitative modelling practices, metamodelling, and capability confidence of biology undergraduate students
Bibliographic Data
| ID | 21589418 |
|---|---|
| Authors | Joseph Dauer (0000-0002-8971-0441, University of Nebraska–Lincoln, corresponding author), Robert L Mayes (0000-0003-2726-2409, Georgia Southern University), Kent Rittschof (0000-0003-3213-7266, Georgia Southern University), Bryon Gallant (Georgia Southern University) |
| Year | 2021 |
| Volume | 43 |
| Issue | 10 |
| Pages | 1685-1707 |
| Publication date | 2021-07-03 |
| Peer Reviewed | Yes |
| Open Access | No |
| Type | ARTICLE |
| Venue | International Journal of Science Education, Part B (JOURNAL) |
| Journal identifiers | ISSN: 2154-8455 • E-ISSN: 2154-8463 |
| Publisher | Informa UK Limited (PUBLISHER • GB) |
| DOI | 10.1080/09500693.2021.1928325 |
| OpenAlex | W3165557185 |
| Language | EN |
| Citations received | 5 |
| References cited | 53 |
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 reasoning within biology and to determine how capable those students felt about this ability. A Rasch analysis was used to construct linear measures and provide validity evidence for the assessment and to examine item statistics on the same scale as student ability measures. Students overall had greater ability in quantitative literacy than in quantitative interpretation of models or modelling. There was no effect of class standing (Freshmen, Sophomore, etc.) on student performance. The assessment showed that students who participated felt confidence in their ability to quantitatively model biological phenomena, even while their performance on ability questions were low. Collectively modelling practices were correlated with students’ metamodelling knowledge and not correlated with students’ modelling capability confidence. Biology instructors who incorporate the process of modelling into their courses may see improved abilities of students to perform on quantitative modelling tasks
Developmental psychology · Mathematics education · Rasch model · Computer Science · Genetics, Bioinformatics, and Biomedical Research · Psychology · Science Education and Pedagogy · Statistics Education and Methodologies · Artificial Intelligence
Model-based reasoning in STEM education
Improvement of Quantitative Reasoning Skills in Transfer and Direct Entry Students Exposed to Cell Biology Modules
Models and the Nature of Science
Why most definitions of modeling competence in science education fall short
Development of the Quantitative Modelling Observation Protocol (QMOP) for undergraduate biology courses
Rasch Analysis in the Human Sciences
Applying the Rasch Model
Invariant Measurement
Developing a learning progression for scientific modeling
Beyond the scientific method
Title unavailable
The Cambridge Handbook of the Learning Sciences
Students’ achievement values, goal orientations, and interest
A rating formulation for ordered response categories
Unskilled and unaware of it
| Unique citing works | 5 |
|---|---|
| Citations per year | 1 |
| Citation span | 2021 - 2026 (6) |
| Citation velocity | current |
| Highly cited | No |
| Citation types | Neutral: 5 |