Design thinking (DT), widely recognized as a structured method for fostering creativity and innovation, has gained significant traction in research and practice across various disciplines. However, with the rise of disruptive technologies like artificial intelligence (AI), DT practices are gradually evolving, reshaping the innovation process. This study investigates the effectiveness of integrating generative AI into a product design thinking activity, employing a single-group pretest-posttest design (i.e., without a control group). The time interval between pretest and posttest measurements was four hours, coinciding with the duration of the DT activity. Conducted in a chemical engineering course at a private university in central Mexico, the research tasked nine students of average academic performance with designing a new beverage. Over a four-hour session, students used AI tools-ChatGPT, Perplexity, and Gemini-at various stages of the design process, including empathy mapping, need statements, idea classification, hills writing, and storyboarding. Several multidimensional constructs were measured using self-report questionnaires to assess the key attributes that DT stimulates: perceptions of creative self-efficacy, design thinking mindset, and empathy. Additionally, the study explored students' views on the usefulness of generative AI and their intention to use such tools. It was hypothesized that post-test scores for each construct would increase. The analysis involved two phases: first, psychometric indicators (alpha reliability) were obtained; second, a statistical approach for assessing individual change was applied, precisely the standardized individual difference (SID). The SID was set at a nominal level of 0.80 (right tail of the normal distribution). Scores with unacceptable measurement error (alpha <. 60) were excluded from the primary analysis. The results revealed a significant increase in students' perceived usefulness of AI between pre- and post-experiment measurements, with a moderate improvement in affective empathy. Other constructs also showed consistent, though modest, post-test score increases. However, only a few participants exceeded the SID threshold, indicating individual variations in response to the intervention. These preliminary findings highlight AI's potential to enhance student creativity through idea generation and expand their consideration of the end user in product design. The results provide valuable insights and recommendations for integrating AI into innovation-driven projects using the design thinking approach and implementing a single-group pretest-posttest design with short time intervals.

The rapid advancement of artificial intelligence (AI) has significantly impacted education by providing personalized and efficient learning experiences. AI tools like chatbots are increasingly used to support student learning, simplifying complex concepts and offering real-time assistance. Despite widespread research on AI in education, its application within Bloom's taxonomy remains underexplored, particularly in STEM fields. This study aims to address this gap by examining the effectiveness of ChatGPT in developing higher-order cognitive skills among engineering students. Specifically, the research investigates ChatGPT's use as a support tool in a chemical engineering course at a private university in central Mexico. The activity was designed to analyze the intention to use ChatGPT and the perception of utility through a didactic strategy aligned with the higher levels of Bloom's taxonomy. The plan involved applying sustainability criteria to improve chemical processes. The study employed a single-group pretest-posttest design, with assessments conducted one week apart. Group-level changes were evaluated using measures of central tendency (mean and median) and variability. In contrast, individual-level changes were assessed using the standardized individual difference and the reliable change index at a nominal alpha level of 0.85, adjusted for practice effects. Results revealed that ChatGPT effectively supports students' understanding at lower and higher levels of Bloom's taxonomy, including skills such as analyzing, creating, and optimizing. The group-level results suggest an overall rise in the measured constructs and consistency in student responses. Between 10% and 19% of participants individually demonstrated improvements in the measured constructs. Additionally, the psychometric properties of the assessments showed satisfactory reliability (with scores equal to or greater than 0.85) and dimensionality. This study highlights AI's potential to enhance learning, particularly in promoting skills aligned with Bloom's higher cognitive levels. However, further empirical research is needed to validate AI's effectiveness in fostering these skills, especially in STEM education. Future studies should also explore the ethical implications of AI in educational contexts and its role in supporting responsible, critical engagement among learners.

The article explores the transformative impact of gamification in education, highlighting the integration of theory and practice to create dynamic and engaging learning experiences using multi-sensory virtual reality environments, such as the Multi-Sensory Virtual Decision-Making Center (MVDC). Among the state of the art of gamification, it has been shown that gamification significantly improves students' attention, motivation, and knowledge acquisition, leading to better academic performance. In addition, it promotes the use of new technologies and encourages teamwork. The Multi-sensory Virtual Decision-Making Center facilitates the creation of immersive collaborative virtual environments where multiple decision-makers can participate remotely in real-time without losing the sense of presence, thus providing an enhanced user experience by conducting joint decision-making sessions remotely and in real-time. Therefore, this work proposes a novel approach to engineering education by combining the synergistic potential of gamification and MVDC, improving both the educational experience and the efficiency of remote and real-time collaborative decision-making. This proposal includes the realization of joint exercises in the classroom with the combination of these technological tools. The initial results are encouraging because they offer an improved user experience when performing collaborative gamification exercises in the classroom and promote efficient and engaging real-time remote decision-making. This work will provide valuable insights and recommendations for future research in this dynamic and promising field.

In recent years, research has emphasized a widening skills gap between job requirements and graduate qualifications. This gap hinders university-to-industry transitions, exacerbating unemployment and talent shortages. Tecnologico de Monterrey introduced TEC21 in 2019, an educational model emphasizing challenge-based and competency-based learning to tackle these issues. A qualitative research design with semi-structured interviews was used to explore the college-to-work transition experience of ten third-year engineering students. The present research reports their perceptions during internships regarding the gains and tools enhanced by the educational model toward improved performance at professional practice within the industry. We analyzed the seven transversal competencies postulated by TEC21. As a result of this exploratory study, participants reported that this model could be considered effective training for improved internship performance. Results included the competencies that students identified as relevant to their professional practice and their level of proficiency in each competency (incipient, intermediate, or advanced). Beyond the limitations of the research, these results contribute to the broader discourse on bridging the gap between academic and industry competencies and highlight the need for incorporating continuous improvement systems to increase the adaptability of the educational models to the fast-evolving requirements of Industry 4.0. Moreover, they could inspire other higher education institutions to implement similar methodologies to keep up with the changing demands of the labor market and continue to be a driving force for societal improvement.