Humberto - Martínez-Huerta

This study examines the validity of the Spanish version of the Scientific Epistemic Beliefs (SEB) Questionnaire among university students in northeastern Mexico, considering multiple sources of evidence. The SEB measures four dimensions of epistemic beliefs: Source, Certainty, Development, and Justification. Data from pilot (n = 150) and main (n = 791) samples were analyzed using Exploratory and Confirmatory Factor Analyses (EFA, CFA), Item Response Theory (IRT), and Differential Item Functioning (DIF). The results provided evidence consistent with a four-factor model, with adequate internal consistency (α = 0.85) and acceptable-to-good fit indices (CFI = 0.944, TLI = 0.936, RMSEA = 0.067, SRMR = 0.071) for a 22-item scale. IRT analyses indicated strong item discrimination, with Source and Certainty covering a broad range of the latent trait, while Development and Justification were more informative at lower to moderate levels. DIF analyses indicated negligible differences in item functioning by gender and academic semester, with minor DIF detected across faculties. Non-parametric analyses identified statistically significant but small differences, with females scoring slightly higher across all dimensions and variations also observed across academic semesters and faculties. Descriptive comparisons with published international data provide contextual evidence within a broader cross-cultural framework.

Axion-like particles (ALPs) are hypothetical particles and compelling candidates for cold dark matter. Their existence could be probed through their conversions into photons in the presence of magnetic fields. In this work, we explore the effect of these photon-ALP conversions by searching for an attenuation in the observed gamma ray spectra of galactic sources that emit at energies of hundreds of TeV. We analyze data from the High-Altitude Water Cherenkov (HAWC) Observatory for the source 3HWC J1908+063. No evidence of photon-ALP conversions was found, and we set constraints on the ALP parameter space. Specifically, we derive exclusion limits for ALPs with masses in the range 10 ^-8 eV ≤ m _a ≤ 10 ^-6 eV and photon-ALP couplings in the range 10 ^-12 GeV ^-1 ≤ g _aγ ≤ 10 ^-10 GeV ^-1 , based on HAWC observations.

Dwarf spheroidal galaxies (dSphs) are excellent targets for indirect dark matter (DM) searches using gamma-ray telescopes because they are thought to have high DM content and a low astrophysical background. The sensitivity of these searches is improved by combining the observations of dSphs made by different gamma-ray telescopes. We present the results of a combined search by the most sensitive currently operating gamma-ray telescopes, namely: the satellite-borne Fermi -LAT telescope; the ground-based imaging atmospheric Cherenkov telescope arrays H.E.S.S., MAGIC, and VERITAS; and the HAWC water Cherenkov detector. Individual datasets were analyzed using a common statistical approach. Results were subsequently combined via a global joint likelihood analysis. We obtain constraints on the velocity-weighted cross section 〈 σv 〉 for DM self-annihilation as a function of the DM particle mass. This five-instrument combination allows the derivation of up to 2-3 times more constraining upper limits on 〈 σv 〉 than the individual results over a wide mass range spanning from 5 GeV to 100 TeV. Depending on the DM content modeling, the 95% confidence level observed limits reach 1.5×10 ^-24 cm ³ s ^-1 and 3.2×10 ^-25 cm ³ s ^-1 , respectively, in the τ ⁺ τ ^- annihilation channel for a DM mass of 2 TeV.

This classroom-based case study examines how an AI-mediated Socratic dialogue, implemented through ChatGPT, can support students’ engagement and perceived learning in undergraduate thermodynamics. Conducted in a first-year engineering physics course at a private university in northern Mexico, the activity invited small student groups to interact with structured prompts designed to promote inquiry, collaboration, and reflective reasoning about the adiabatic process. Rather than functioning as a source of answers, ChatGPT was intentionally positioned as a mediating scaffold for Socratic questioning, prompting students to articulate, examine, and refine their reasoning. A mixed-methods approach was employed, combining a 10-item Likert-scale survey with construct-level statistical analysis of two focal dimensions: perception of learning and engagement, including an exploratory comparison by gender. Results indicated consistently high levels of perceived learning and engagement across the cohort, with average scores above 4.5 out of 5. At the construct level, no statistically significant gender differences were observed, although a single item revealed higher perceived learning among female students. Overall, the findings suggest that the educational value of ChatGPT in this context emerged from its integration within a Socratic, inquiry-oriented pedagogical design, rather than from the technology alone. These results contribute to ongoing discussions on the responsible and pedagogically grounded integration of generative AI in physics education and align with Sustainable Development Goal 4 (Quality Education).

This study examines pseudoscientific beliefs among university students, focusing on gender and faculty differences at a private university in northeastern Mexico. Data were collected from 794 students (38% male, 62% female) across six academic disciplines using the Pseudoscience Endorsement Scale (PES). Statistical analyses included the Kruskal–Wallis test to assess group differences and the Wilcoxon rank sum test for pairwise comparisons. Results revealed significant gender differences (p < 0.001), with female students scoring higher. Scores also varied significantly across faculties (p < 0.001), with students in Business and Arts, Architecture, and Design exhibiting the highest levels of endorsement of pseudoscientific beliefs. In contrast, those in Engineering and Technology scored the lowest. These findings underscore the need for targeted educational interventions to mitigate pseudoscientific beliefs and enhance students’ understanding of STEM fields. The study aligns with the United Nations’ Sustainable Development Goal 4, which advocates for inclusive, equitable, and quality education that fosters critical thinking and lifelong learning. It emphasizes the importance of accounting for gender and academic background when addressing students’ belief systems.

Inspired by the principles of quantum mechanics, we constructed a model of students’ misconceptions about heat and temperature, conceptualized as a quantum system represented by a density matrix. Within this framework, the presence or absence of misconceptions is delineated as pure states, while the probability of mixed states is also considered, providing valuable insights into students’ cognition based on the mental models they employ when holding misconceptions. Using the analysis model previously employed by Lei Bao and Edward Redish, we represented these results in a density matrix. In our research, we utilized the Zeo and Zadnik Thermal Concept Evaluation among 282 students from a private university in Northeast Mexico. Our objective was to extract information from the analysis of multiple-choice questions designed to explore preconceptions, offering valuable educational insights beyond the typical Correct–Incorrect binary analysis of classical systems. Our findings reveal a probability of 0.72 for the appearance of misconceptions, 0.28 for their absence, and 0.43 for mixed states, while no significant disparities were observed based on gender or scholarship status, a notable difference was observed among programs (p < 0.05). These results are consistent with the previous literature, confirming a prevalence of misconceptions within the student population.

Progress has been made in recent decades toward achieving gender equality, but today, the gender gap is still noticeable, especially in STEM fields. In support of Goal 5 of the 2030 Sustainable Development Agenda: achieve gender equality and empower all women and girls, we analyze the context of a private university in northeastern Mexico using a sample of 249 students (157 males and 92 females) enrolled in the first-year engineering course Physics I. The sample presents better academic performance in favor of women by the end of the course as reported through the final course score (F); thus, we explore potential gender differences in student profiles, such as their motivation and level of procrastination using Kruskal–Wallis correlation tests, and measuring the effect size with Cohen’s d. Our tests reported here reveal significant differences in extrinsic motivation (EMO) and intrinsic motivation (IMO), where females obtained higher means in IMO, while males reported higher levels of procrastination (PRO). Contrary to other cases in the literature, the sample presents better academic performance in favor of women. Our findings here aim to encourage programs and strategies that strengthen women’s intrinsic motivation to support women’s empowerment and keep reducing the gender gap.