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1. A Principled Approach to Designing Assessments That Integrate Science and Computational Thinking

   https://doi.org/10.22318/cscl2018.384  

   Basu, S.; McElhaney, K. W.; Grover, S.; Harris, C. J.; Biswas, G. (July 2018, 13th International Conference of the Learning Sciences (ICLS))

   There is increasing interest in broadening participation in computational thinking (CT) by integrating CT into pre-college STEM curricula and instruction. Science, in particular, is emerging as an important discipline to support integrated learning. This highlights the need for carefully designed assessments targeting the integration of science and CT to help teachers and researchers gauge students’ proficiency with integrating the disciplines. We describe a principled design process to develop assessment tasks and rubrics that integrate concepts and practices across science, CT, and computational modeling. We conducted a pilot study with 10 high school students who responded to integrative assessment tasks as part of a physics-based computational modeling unit. Our findings indicate that the tasks and rubrics successfully elicit both Physics and CT constructs while distinguishing important aspects of proficiency related to the two disciplines. This work illustrates the promise of using such assessments formatively in integrated STEM and computing learning contexts. 

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2. LearnLens: An AI-Enhanced Dashboard to Support Teachers in Open-Ended Classrooms

   Srivastava, N; Jain, S; Cohn, C; Mohammed, N; Timalsina, U; Biswas, G (July 2025, Workshop on Advances in Artificial Intelligence for Exploratory Learning (AI4EXL) (https://transeet.eu/ai4exl/))

   Mavrikis, M; Lalle, S; Azevedo, R; Biswas, G; Roll, I (Ed.)

   Exploratory learning environments (ELEs), such as simulation-based platforms and open-ended science curricula, promote hands-on exploration and problem-solving but make it difficult for teachers to gain timely insights into students' conceptual understanding. This paper presents LearnLens, a generative AI (GenAI)-enhanced teacher-facing dashboard designed to support problem-based instruction in middle school science. LearnLens processes students' open-ended responses from digital assessments to provide various insights, including sample responses, word clouds, bar charts, and AI-generated summaries. These features elucidate students' thinking, enabling teachers to adjust their instruction based on emerging patterns of understanding. The dashboard was informed by teacher input during professional development sessions and implemented within a middle school Earth science curriculum. We report insights from teacher interviews that highlight the dashboard's usability and potential to guide teachers' instruction in the classroom. 

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3. Enabling factors and barriers for adopting engineering curricula in high schools: School, district, and state administrator perspectives

   Dalal, M.; Carberry, A. (July 2021, 2021 ASEE Annual Conference and Exposition)

   null (Ed.)

   Pre-college engineering education has been on a sharp rise in the United States. Numerous schools offer some variation of an engineering curricula, but challenges remain regarding socio-cultural perceptions of engineering, teacher training, curricular alignment with state standards, and policy decisions. Many past studies have examined students’ and teachers’ knowledge, perceptions, and beliefs regarding pre-college engineering instruction. Few studies have investigated the viewpoints of school administrators, or state and district personnel. This qualitative study investigated perspectives of three such administrators in a southwest US public high school. The school was one of nine pilot locations offering a new engineering course designed to ‘demystify’ engineering for high school students and teachers from all walks of life. Results converged around four major themes: 1) relevance and current state of pre-college engineering education, 2) teacher certification and professional development, 3) industry connections, and 4) expectations of pre-college engineering curricula. The resulting themes shed light on long standing issues affecting adoption of engineering at the pre-college level and highlight a few areas that upcoming pre-college engineering education programs could focus on. 

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4. Expanding opportunities to learn in secondary science classrooms using unconventional forms of classroom assessments

   https://doi.org/10.1002/tea.21824  

   Kang, Hosun; Talafian, Hamideh; Tschida, Paul (October 2022, Journal of Research in Science Teaching)

   Abstract This study explores the role of unconventional forms of classroom assessments in expanding minoritized students' opportunities to learn (OTL) in high school physics classrooms. In this research + practice partnership project, high school physics teachers and researchers co‐designed a unit about momentum to expand minoritized students' meaningful OTL. Specifically, the unit was designed to (a) expand what it means to learn and be good at science using unconventional forms of assessment, (b) facilitate students to leverage everyday experiences, concerns, and home languages to do science, and (c) support teachers to facilitate meaningful dialogical interactions. The analysis focused on examining minoritized students' OTLs mediated by intentionally designed, curriculum‐embedded, unconventional forms of assessments. The participants were a total of 76 students in 11th or 12th grade. Data were gathered in the form of student assessment tasks, a science identity survey, and interviews. Data analysis entailed: (a) statistical analysis of student performance measured by conventional and unconventional assessments and (b) qualitative analysis of two Latinx students' experiences with the co‐designed curriculum and assessments. The findings suggest that the use of unconventional forms of curriculum‐embedded assessment can increase minoritized students' OTLifthe assessment facilitates minoritized students to personally and deeply relate themselves to academic tasks. 

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5. Long-Term Outcomes of RET Programs on Female and Minority Student High School Graduation Rates and Undergraduate STEM Major Rates (Fundamental)

   Nichol, C.; Crawford, C. A.; Barr, C.; Cerda, I. (January 2021, ASEE Annual Conference proceedings)

   null (Ed.)

   Research Experience for Teachers (RET) programs are National Science Foundation (NSF) funded programs designed to provide K- 12 Science, Technology, Engineering, and Mathematics (STEM) teachers with immersive, hands-on research experiences at Universities around the country. The NSF RET in nanotechnology encourages teachers to translate cutting-edge research into culturally relevant Project-Based Learning (PjBL) and engineering curriculum. Traditionally, the evaluation of RET programs focuses on the growth and development of teacher self-efficacy, engineering content knowledge gains, or classroom implementation of developed curriculum materials. However, reported methods for evaluating the impact of RETs on their female, minority student populations' high school graduation and undergraduate STEM major rates are limited. This study's objective was to compare RET high school student graduation rates and undergraduate STEM major rates across gender, race, and ethnicity to a comparison sample to determine the RET program's long-term impact on students' likelihood of pursuing STEM careers. The approach of collecting and analyzing the Texas Education Research Center Database (EdRC) data is a novel methodology for assessing RET programs' effectiveness on students. The EdRC is a repository of K-12 student data from the Texas Education Agency (TEA) and Higher Education data from the Texas Higher Education Coordinating Board (THECB). This joint database contains demographic, course registration, graduation, standardized testing, and college major, among others, for all students that attended a K-12 public school in Texas and any college in Texas, public or private. The RET program participants at Rice University (2010 – 2018) taught numerous students, a sample size of 11,240 students. A propensity score matching generated the student comparison group within the database. Students' school campus, gender, race/ethnic status, and English proficiency status were applied to produce a graduation comparison sample size of 11,240 students of Non-RET participants. Linking the TEA database to the THECB database resulted in college STEM participants and comparison sample sizes of 4,029 students. The project team conducted a logistic regression using RET status to predict high school graduation rates as a whole and by individual variables: gender, Asian American, Black, Caucasian, and Latinx students. All models were significant at p less than 0.05, with models in favor of students RET teachers. The project team conducted a logistic regression using RET status to predict student STEM undergraduate major rates as a whole and by individual variables: Gender, Asian American, Black, Caucasian, and Latinx students. African American and Caucasian models were significant at p less than 0.05; Gender, Asian American, and Latinx models were marginally significant (0.05 less than p greater than 0.1), where RET students had higher STEM major rates than matched controls. The findings demonstrate that RET programs have a long-term positive impact on the students' high school graduation rates and undergraduate STEM major rates. As teachers who participate in the RET programs are more likely to conduct courses using PjBL strategies and incorporate real-world engineering practices, female and minority students are more likely to benefit from these practices and seek careers utilizing these skills. 

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