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1. Parag Pathak: Winner of the 2018 Clark Medal

   https://doi.org/https://doi.org/10.1257/jep.31.1.231  

   Pakes, Ariel; Sobel, Joel (January 2019, The Journal of economic perspectives)

   The 2018 John Bates Clark medal of the American Economic Association was awarded to Parag Pathak for his contributions to our understanding of the impacts of educational policies. Both the theory and the empirical research was notable for taking the constraints facing administrators seriously. As a result, Parag’s research led directly to educational reforms in many large U.S. cities and abroad. The leading example is Parag (and co-author’s) research on school assignment mechanisms which led many school districts to institute fairer and more efficient procedures for allocating students to schools. The institutional detail Parag learned in working on the assignment problem led to innovative empirical work on the impacts of different types of schools, most notably of charters, which was suggestive of the characteristics of both successful schools and of the types of students who gained from being enrolled in them. His recent work utilizes the data that has been generated by the new assignment rules to provide complete frameworks for the quantitative analysis of the benefits of different assignment mechanisms, and has an enlightening demonstration of those benefits in New York high schools. 

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2. Practitioner Perspectives on COVID-19’s Impact on Computer Science Education Among High Schools Serving Students from Lower and Higher Income Families

   https://doi.org/10.1145/3557047  

   McGill, Monica M.; Snow, Eric; Vaval, Luronne; DeLyser, Leigh Ann; Wortel-London, Stephanie; Thompson, Angelica (January 2022, ACM Transactions on Computing Education)

   Research Problem. Computer science (CS) education researchers conducting studies that target high school students have likely seen their studies impacted by COVID-19. Interpreting research findings impacted by COVID-19 presents unique challenges that will require a deeper understanding as to how the pandemic has affected underserved and underrepresented students studying or unable to study computing. Research Question. Our research question for this study was: In what ways has the high school computer science educational ecosystem for students been impacted by COVID-19, particularly when comparing schools based on relative socioeconomic status of a majority of students? Methodology. We used an exploratory sequential mixed methods study to understand the types of impacts high school CS educators have seen in their practice over the past year using the CAPE theoretical dissaggregation framework to measure schools’ Capacity to offer CS, student Access to CS education, student Participation in CS, and Experiences of students taking CS. Data Collection Procedure. We developed an instrument to collect qualitative data from open-ended questions, then collected data from CS high school educators (n = 21) and coded them across CAPE. We used the codes to create a quantitative instrument. We collected data from a wider set of CS high school educators ( n = 185), analyzed the data, and considered how these findings shape research conducted over the last year. Findings. Overall, practitioner perspectives revealed that capacity for CS Funding, Policy & Curriculum in both types of schools grew during the pandemic, while the capacity to offer physical and human resources decreased. While access to extracurricular activities decreased, there was still a significant increase in the number of CS courses offered. Fewer girls took CS courses and attendance decreased. Student learning and engagement in CS courses were significantly impacted, while other noncognitive factors like interest in CS and relevance of technology saw increases. Practitioner perspectives also indicated that schools serving students from lower-income families had 1) a greater decrease in the number of students who received information about CS/CTE pathways; 2) a greater decrease in the number of girls enrolled in CS classes; 3) a greater decrease in the number of students receiving college credit for dual-credit CS courses; 4) a greater decrease in student attendance; and 5) a greater decrease in the number of students interested in taking additional CS courses. On the flip-side, schools serving students from higher income families had significantly higher increases in the number of students interested in taking additional CS courses. 

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3. “What Makes ChatGPT Dangerous is Also What Makes It Special”: High-School Student Perspectives on the Integration or Ban of Artificial Intelligence in Educational Contexts

   https://doi.org/10.46328/ijte.651  

   Famaye, Tolulope; Bailey, Cinamon Sunrise; Adisa, Ibrahim; Arastoopour Irgens, Golnaz (March 2024, International Journal of Technology in Education)

   The emergence of ChatGPT, an AI-powered language model, has sparked numerous debates and discussions. In educational research, scholars have raised significant questions regarding the potential, limitations, and ethical concerns around the use of this technology. While research on the application and implications of ChatGPT in academic settings exists, analysis of the perspectives of high-school students are limited. In this study, we use qualitative content analysis to explore the perspectives of high-school students regarding the integration or ban of ChatGPT in their schools through the lens of the Technology Acceptance Model (TAM2). Data was sourced from students’ comments to a New York Times Learning Network article. Findings revealed that students' perceptions about integrating or banning ChatGPT in schools are influenced by their assessments of the technology’s usefulness, personal experiences, societal technology trends, and ethical considerations. Our findings suggest that student perspectives in this study align with those of educators and policymakers while also possessing unique perspectives that cater to their specific needs and experiences. Implications emphasize the significance of an inclusive decision-making process around the integration of AI schools in educational contexts, including students alongside other stakeholders. 

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4. Encouraging STEM Careers among Minoritized High School Students: The Interplay between Socio-Environmental Factors and Other Social Cognitive Career Constructs

   https://doi.org/10.3390/educsci14070789  

   Durham, Rachel E; Falk, Michael L; Daniels, Alexis G; Reigel, Allison; Sparks, Alisha; Williams, Margo; Yanisko, Emily J (July 2024, Education Sciences)

   Performance in math, particularly algebra, is a major barrier to student success and participation in STEM among under-represented minoritized students, particularly Black U.S. high school students. This research applies social cognitive career theory (SCCT) to measure the impacts of an afterschool algebra for engineering program on math self-efficacy and interest in STEM among high school students in a large urban district. To study the program’s effects, a mixed methods research design was used where schools were assigned to either treatment or control conditions. Students in treatment schools accessed algebra for engineering modules, STEM professional role model videos, and field trips, while students in control schools accessed role model videos and field trips only. Surveys measuring math self-efficacy and STEM interest, outcome expectations, and choice goals were completed by participants in both conditions at the beginning and end of two separate program years, 2021–2022 and 2022–2023. Across both years, quantitative results suggest some positive effects of participation, particularly for STEM choice goals, but benefits depend upon student participation levels. Qualitative data offer student voice around prior experiences in math and science and the development of postsecondary plans in STEM. In combination, the results suggest that for students who do not initially identify as STEM career-bound, afterschool programming may not necessarily promote preparation for STEM careers due to an accumulation of weak math and science school experiences and other socio-environmental influences. 

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5. Why Does a Growth Mindset Intervention Impact Achievement Differently across Secondary Schools? Unpacking the Causal Mediation Mechanism from a National Multisite Randomized Experiment

   https://doi.org/10.1080/19345747.2021.1894520  

   Qin, X. (June 2021, Journal of research on educational effectiveness)

   The growth mindset or the belief that intelligence is malleable has garnered significant attention for its positive association with academic success. Several recent randomized trials, including the National Study of Learning Mindsets (NSLM), have been conducted to understand why, for whom, and under what contexts a growth mindset intervention can promote beneficial achievement outcomes during critical educational transitions. Prior research suggests that the NSLM intervention was particularly effective in improving low-achieving 9th graders’ GPA, while the impact varied across schools. In this study, we investigated the underlying causal mediation mechanism that might explain this impact and how the mechanism varied across different types of schools. By extending a recently developed weighting method for multisite causal mediation analysis, the analysis enhances the external and internal validity of the results. We found that challenge-seeking behavior played a significant mediating role, only in medium-achieving schools, which may partly explain the reason why the intervention worked differently across schools. We conclude by discussing implications for designing interventions that not only promote students’ growth mindsets but also foster supportive learning environments under different school contexts. 

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