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Abstract The current study explores the quality of students’ argumentation within the context of Adaptive Comparative Judgment (ACJ) and Learning by Evaluation (LbE), focusing on the Claim-Evidence-Reasoning (CER) framework. The aim is to understand what students consider essential for superior engineering design journals and why, particularly examining evidence and reasoning components. Thirty-five students from four high schools participated in LbE, justifying their preferences for selected options. These schools were part of a broader five-school project, though one did not conduct the relevant session and was excluded from the study. Utilizing the CER framework, the study analyzed the structure of scientific argumentation, supplemented by thematic analysis to elucidate students' reasoning. Three response models emerged: Claim-Evidence (CE), Claim-Reasoning (CR), and CER. CE responses lacked reasoning, while CR responses lacked evidence. Students favored design portfolios with visual aids, detailed content, documentation of design failures, and clearly stated challenges. For reasoning, students highlighted the value of clear explanations of the design process, facilitation of group and individual work, idea generation, and instructional clarity. The study underscores the importance of teacher-led scaffolding to help students articulate comprehensive claims and suggests structured group discussions and modeling as effective supports. 

Adaptive comparative judgment (ACJ) has been widely used to evaluate classroom artifacts with reliability and validity. In the ACJ experience we examined, students were provided a pair of images related to backpack design. For each pair, students were required to select which image could help them ideate better. Then, they were prompted to provide a justification for their decision. Data were from 15 high school students taking engineering design courses. The current study investigated how students’ reasoning differed based on selection. Researchers analyzed the comments in two ways: (1) computer-aided quantitative content analysis and (2) qualitative content analysis. In the first analysis, we performed sentiment analysis and word frequency analysis using natural language processing. Based on the findings, we explored how the design thinking process was embedded in student reasoning, and if the reasoning varied depending on the claim. Results from sentiment analysis showed that students tend to reveal more strong positive sentiment with short comments when providing reasoning for the selected design. In contrast, when providing reasoning for those items not chosen, results showed a weaker negative sentiment with more detailed reasons. Findings from word frequency analysis showed that students valued the function of design as well as the user perspective, specifically, convenience. Additionally, students took aesthetic features of each design into consideration when identifying the best of the two pairs. Within the engineering design thinking context, we found students empathize by identifying themselves as users, define user’s needs, and ideate products from provided examples. 

This research investigates students’ argumentation quality in engineering design thinking. We implemented Learning by Evaluating (LbE) using Adaptive Comparative Judgment (ACJ), where students assess pairs of items to determine the superior one. In ACJ, students provided rationales for their critiques, explaining their selections. Fifteen students participated in an LbE exercise before starting their backpack design projects, critically evaluating multiple backpack designs and producing 145 comments. Writing comments required students to discern and justify the superior design, fostering informed judgment and articulation of their reasoning. The study used the Claim, Evidence, and Reasoning (CER) framework, adapted for engineering design thinking, to analyse these critiques. The framework emphasized three aspects: Empathy (understanding user needs), Ideation (deriving design inspiration), and Insight (gaining valuable understanding from evaluated designs). We employed both deductive and inductive content analysis to evaluate the argumentation quality in students’ critiques. High-quality argumentation was identified based on six codes: user-focused empathy, design inspirations, logical rationalizations, multi-criteria evaluations, aesthetic considerations, and cultural awareness. Poor-quality argumentation lacked these elements and was characterized by vagueness, uncertainty, brevity, inappropriateness, irrelevance, gender bias, and cultural stereotyping. By identifying critical elements of effective argumentation and common challenges students may face, this study aims to enhance argumentation skills in engineering design thinking at the secondary education level. These insights are intended to help educators prepare students for insightful and successful argumentation in engineering design projects. 

Peer review and the evaluation of samples are common tools used in education and our research has shown positive impacts on student learning through the intentional evaluation of samples as a priming exercise—an experience we have termed “Learning by Evaluating (LbE).” While previous work in design and technology (D&T) classrooms with LbE has demonstrated positive student learning gains, we have not yet investigated the impact of the classroom teacher on the LbE experience for students. Therefore, our research sought to analyze the impact of a classroom teacher on student experience within a LbE experience situated in a D&T classroom. To better understand the impact the teacher has during LbE, multiple D&T classrooms engaged in LbE sessions were enrolled in this study. Each D&T classroom followed a similar protocol which had students engaged in an open-ended design problem who used LbE to evaluate samples of related work as part of their designing process. Specifically, we collected data from student LbE decisions to explore if students in different D&T classes valued different elements of the samples (e.g., did students in one class focus on aesthetics while students in another emphasized brevity in explanations). An online software platform (RMCompare) was used to engage students in LbE and collect both the quantitative data associated with the ranked preferences of the students and the qualitative data from their justifications for their selections. All students were enrolled in the same district-level course and presented with the same samples. Key findings—both similarities and differences—between classes will 

The COVID-19 pandemic forced universities to suspend face-to-face instruction, prompting a rapid transition to online education. As many lab courses transitioned online, this provided a rare window of opportunity to learn about the challenges and affordances that the online lab experiences created for students and instructors. We present results from exploratory educational research that investigated student motivation and self-regulated learning in the online lab environment. We consider two student factors: motivation and self-regulation. The instrument is administered to students (n = 121) at the beginning of the semester and statistically analysed for comparisons between different demographic groups. The results indicated students' major was the only distinguishing factor for their motivation and self-regulation. Students' unfamiliarity with online labs or uncertainty about what to expect in the course contributed to the lower levels of self-regulation. The lack of significant differences between various subgroups was not surprising, as we posit many students entered the virtual lab environment with the same level of online lab experience. We conducted interviews among these respondents to explore the factors in greater detail. Using latent Dirichlet allocation, three main topics that emerged: (1) Learning Compatibility, (2) Questions and Inquiry, and (3) Planning and Coordination. 

The bulk photovoltaic effect (BPE) has drawn considerable attention due to its ability to generate photovoltages above the bandgap and reports of highly enhanced photovoltaic current when using nanoscale absorbers or nanoscale electrodes, which, however, do not lend themselves to practical, scalable implementation. Herein, it is shown that a strikingly high BPE photoresponse can be achieved in an ordinary thin‐film configuration merely by tuning fundamental ferroelectric properties. Nonmonotonic dependence of the responsivity (R_SC) on the ferroelectric polarization is observed and at the optimal value of the film polarization, a more than three orders of magnitude increase in theR_SCfrom the bulk BaTiO₃value is obtained, reachingR_SCclose to 10⁻² A W⁻¹, the highest value reported to date for the archetypical ferroelectric BaTiO₃films. Results challenge the applicability of standard first‐principles‐based descriptions of BPE to thin films and the inherent weakness of BPE in ferroelectric thin films.