The Effects of a Model-Based Physics Curriculum Program with a Physics First Approach: a Causal-Comparative Study

Liang, Ling L.; Fulmer, Gavin W.; Majerich, David M.; Clevenstine, Richard F.; Howanski, Raymond

doi:10.1007/s10956-011-9287-2

Cited by 27 publications

(29 citation statements)

References 22 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…These students noted that they would have preferred having lectures or studying the material from the textbook over interacting with the computational models. Our results are consistent with previous findings that classroom interactions and student confidence in the results obtained with models can affect the success of computer model-based instructional approaches (29,34). Some students reported usability issues and commented on their lack of prior knowledge as being challenges to their learning with the modules.…”

Section: Discussionsupporting

confidence: 93%

“…Computational models of complex biological and biochemical processes and simulations can actively engage students in an experiment-like learning environment (23)(24)(25). Computational model-based learning is leveraged in many fields (e.g., chemistry, physics, engineering, biology) and encourages students to make their thinking explicit, which can help students simultaneously hone practical skills, increase content knowledge, and overcome scientific misconceptions (13,23,(26)(27)(28)(29)(30)(31)(32)(33)(34). Moreover, the need to develop students' science process skills in general, and modeling abilities specifically, extends beyond the classroom, and the use of models to predict experimental outcomes is a recognized learning goal for biochemistry students (2,3,5).…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Using computational modeling to teach metabolism as a dynamic system improves student performance

Song²,

et al. 2020

Preprint

View full text Add to dashboard Cite

Author ContributionsTH, RLR, BAC, and KVD conceived of the concept. CSB, TH, RLR, and KVD designed assessment questions with input from BAC and MEH. CSB designed computational models, developed overall module structure, and collected data. CSB, RLR and KVD designed module questions and refined the module structure with input from TH. MEH and SMS provided instructor-level feedback and RH provided usability feedback about modules. AR and AS built software features. CSB and CS analyzed the data. CSB, TH, RLR, BAC, MEH and KVD provided critical feedback and shaped the research and analysis. CSB, TH, and RLR wrote the manuscript with input from BAC and KVD. All authors commented on the manuscript. AbstractUnderstanding metabolic function requires knowledge of the dynamics, interdependence, and regulation of biochemical networks. However, current approaches are not optimal to develop the needed mechanistic understanding, and misconceptions about biological processes persist even after graduation. To address these issues, we developed a computational modeling and simulation approach that employs scaffolded learning to teach biochemistry students about the regulation of metabolism. The power of the approach lies in students' abilities to alter any component or connection in a modeled system and instantly observe the effects of their changes.We find that students who use our approach perform better on biochemistry metabolism questions compared to students in a course that did not use this approach. We also investigated performance by gender and found that our modules may have the potential to increase equity in education. We noted that students are generally positive about the approach and appreciate its benefits. Our modules provide life science instructors with a dynamic and systems-driven approach to teach metabolic regulation and control that improves learning and also equips students with important technical skills.

show abstract

Section: Discussionsupporting

confidence: 93%

Section: Introductionmentioning

confidence: 99%

Using computational modeling to teach metabolism as a dynamic system improves student performance

Song²,

et al. 2020

Preprint

View full text Add to dashboard Cite

show abstract

“…Thus, modeling has the potential to address many weaknesses of the traditional lecture–demonstration methods, including the fragmentation of knowledge, student passivity, and the persistence of naïve beliefs about the physical world. Research has shown that students’ conceptual understanding of phenomena in physics increases when modeling‐enhanced curriculum is used (Liang, Fulmer, Majerich, Clevenstine, & Howanski, ). In general, elements of a modeling process involve model selection, construction, validation, analysis, deployment, and reconstruction (Jackson, Dukerich, & Hestenes, ; Jong, Chiu, & Chung, ).…”

Section: Literature Reviewmentioning

confidence: 99%

“…Liang et al. () described the importance of scaffolding scientific discourse when using modeling to support students’ understanding, and pointed to scaffolds such as small group work, writing about observations and explanations, presenting work to the rest of the class, and reviewing other groups’ work. It is clear that students, as they are not professional scientists, need support to understand how to construct and use models and, in particular, need help developing the metacognitive skills necessary for understanding the benefits of modeling.…”

Section: Literature Reviewmentioning

confidence: 99%

Modeling strategies enhanced by metacognitive tools in high school physics to support student conceptual trajectories and understanding of electricity

2018

View full text Add to dashboard Cite

Modeling is considered an important scientific practice, and modeling instruction has the potential to support conceptual change in students in physics. However, when students are not taught how to think about modeling, and how to develop and use models, the learning potential of modeling may be limited. This paper argues that the use and explicit teaching of metacognitive tools like interactive questioning and individual reflection increase students' ability to use and make sense of models. We present a sequence of activities incorporating metacognitive tools with a variety of models (mental, physical, simulated, and mathematical) in a high school physics unit of electricity. Using data from classroom observations, individual student reflections, group-created posters, and classroom discussion, we found evidence to demonstrate the complicated nature of conceptual change, the importance of using a variety of different representations (models) of a phenomenon, and the critical role of the teacher in learning. Teachers need to be aware of this process and able to give students the time they need to fully explore and develop multiple models and support to think critically about models. Although many classrooms are limited in time, this process is necessary to move beyond rote memorization toward meaningful conceptual change.

show abstract

“…The first sample consisted of 301 high-school students who participated in a larger comparative study on physics and chemistry instruction (Liang, Fulmer, Majerich, Clevenstine, & Howanski, 2012). The high-school students were in Grades 9 -12 and enrolled in introductory physics courses.…”

Section: Data Sourcesmentioning

confidence: 99%

Applying a Force and Motion Learning Progression over an Extended Time Span using the Force Concept Inventory

Fulmer¹,

Liang

Liu

2014

International Journal of Science Education

Self Cite

View full text Add to dashboard Cite

This exploratory study applied a proposed force and motion learning progression (LP) to highschool and university students and to content involving both one-and two-dimensional force and motion situations. The Force Concept Inventory (FCI) was adapted, based on a previous content analysis and coding of the questions in the FCI in terms of the level descriptors of the LP. Using a Rasch measurement model and latent class analysis, students' responses were tested for fit with the proposed LP. Results indicated that the recoded FCI response options are generally consistent with a progression of difficulties as proposed in the LP, and that the students could be organized into different groups with progressively different levels of ability. However, reliability for the ability estimates was only moderate and response options at lower levels of the LP were not well differentiated. Implications for the assessments with LPs and revisions for both the FCI and the force and motion LP are also discussed.

show abstract

The Effects of a Model-Based Physics Curriculum Program with a Physics First Approach: a Causal-Comparative Study

Cited by 27 publications

References 22 publications

Using computational modeling to teach metabolism as a dynamic system improves student performance

Using computational modeling to teach metabolism as a dynamic system improves student performance

Modeling strategies enhanced by metacognitive tools in high school physics to support student conceptual trajectories and understanding of electricity

Applying a Force and Motion Learning Progression over an Extended Time Span using the Force Concept Inventory

Contact Info

Product

Resources

About