Energy is one of the most central and richly connected ideas across all science disciplines. The purpose of this study was to develop a measurement instrument for assessing students’ understanding of the energy concept within and across different science disciplines. To achieve this goal, the Inter‐Disciplinary Energy concept Assessment (IDEA) was developed through a pilot test, consisting of 49 items presented in pairs: multiple‐choice questions followed by open‐ended justification questions. The IDEA was administered to 356 college students in the United States. The partial credit Rasch model was applied to establish evidence of validity and reliability of measures for the IDEA. Results showed that the IDEA can produce reliable and valid measures of student understanding of the energy concept in different science disciplines. No statistical difference was found between the average difficulties of items across disciplines. In addition, the four science disciplines were positively correlated in terms of student understanding of the energy concept. When item difficulties were analyzed by science content topics, it was found that students have difficulty in understanding the energy concept in atomic structure, wave, electric and magnetic energy, and modern physics content areas. This result suggests that students’ difficulty in understanding the energy concept is compounded with specific science contents.

This paper describes the development of Connected Chemistry as Formative Assessment (CCFA) pedagogy, which integrates three promising teaching and learning approaches, computer models, formative assessments, and learning progressions, to promote student understanding in chemistry. CCFA supports student learning in making connections among the three domains of chemistry: the macroscopic; the submicroscopic; and the representational. There were 10 sets of computer models and computer-model-based formative assessment tests developed for 10 chemistry topics to enhance student understanding of matter and energy, and models. This article reports the development process of CCFA and evidence supporting the reliability and validity of measures of the formative assessment tests in CCFA based on the Rasch measurement application.

No abstract

Background: The paper presents effects of simulation-based formative assessments on students' conceptions in physics. In the study, two topics-motion in two dimensions and conservation of energy-were selected to explore students' conceptions in physics, and related assessment tasks incorporating computer simulations and formative assessment questions were developed. Material and methods: The participant students were first-year college students with majors related to science or engineering. Analytic rubrics were developed to capture the students' normative and non-normative ideas revealed in their responses, and a holistic rubric was applied to categorize the responses into four response models. Results: The results demonstrated that, overall, students predicted and explained the given scientific phenomena with more valid scientific ideas after experiencing a computer simulation. However, the results also indicated that students' non-normative ideas were still present even after experiencing computer simulations, especially when they were required to consider an abstract scientific concept such as energy dissipation. Conclusions: The finding can be explained with knowledge-in-piece perspectives (diSessa, 1993), that students' naïve knowledge is fragmented, and thus they do not demonstrate a coherent understanding of abstract science concepts across different situations.

This study reports the effect of computer models as formative assessment on high school students' understanding of the nature of models. Nine high school teachers integrated computer models and associated formative assessments into their yearlong high school chemistry course. A pre-test and post-test of students' understanding of the nature of models using a published measurement instrument on the nature of models were conducted. A four-step hierarchical multiple regression and a two-level (level 1 – student and level 2 – teacher) hierarchical linear modeling were used to test the effect of the intervention on students' understanding of the nature of models. Our analysis revealed a significant effect of frequencies of using computer models for four of the five sub-scales related to the nature of models. The implications of these findings are that, as students have more experience using computer models in their classroom, they develop a better understanding of the nature of models. However, their understanding of models as multiple representations didn't show a significant improvement, possibly due to the lack of support from teachers, who in turn need both content and pedagogical supports within their teaching.