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This manuscript examines how university coaches can use the Classroom Check-Up (CCU; Reinke et al., 2008) to support continuous school improvement efforts around teacher practice within a PDS model and how collaboration between university faculty can increase their coaching self-efficacy.

The paper is conceptual in that it presents an innovative idea to stimulate discussion, generate new ideas, and advance thinking about supporting educator coaching efficacy in school-university partnerships.

The paper provides insights and ideas for using a collaborative faculty coaching model based on the CCU (Reinke et al., 2008). Each coach provides insight about adapting the model to fit teacher, school, and district needs. Moreover, coaches report on how collaborating impacted their coaching self-efficacy.

This paper fulfills an identified need to support continuous school improvement efforts amid a teaching shortage using a collaborative faculty coaching model. Moreover, the authors explore “coaching self-efficacy” as a rare but valuable construct that is impacted by peer feedback.

In this study, students’ perceptions of the effective practices of their research mentors were examined. The research mentors implemented the practices informed by the Center for the Improvement of Mentored Experiences in Research (CIMER) mentorship competencies to mentor underrepresented students in engineering education research in a virtual environment.

This research experience for undergraduates (REU) program, situated in the United States of America, consisted of undergraduate students (i.e. mentees), graduate students and faculty mentors who all had at least one underrepresented identity in engineering (i.e. Black, Latiné/x, and/or women). Using qualitative methods, we used data from reflection surveys and follow-up interviews with REU mentees to understand the outcomes of the mentorship strategies employed by the mentors in the program. The data were analyzed thematically using CIMER model constructs and social capital theory as guiding frameworks.

The results indicated the identified strategies students perceived as the most impactful for mentorship throughout the program. Students in the REU gained knowledge on how to activate social capital in mentorship relationships and how to better mentor others.

The findings provide insight on how to operationalize the CIMER mentorship competencies to skillfully mentor underrepresented students in engineering. Given the size of the REU and the nature of qualitative research, the sample size was limited.

The results help inform mentorship practices for underrepresented individuals in engineering education and the workforce. Further, they add to the practical knowledge of implementing CIMER best practices virtually, at a time when the world has transitioned to more hybrid and virtual working and learning environments.

This study identifies impactful strategies for operationalizing mentorship strategies informed by theory- and evidence-based CIMER mentorship competencies. In addition, this study extends knowledge about how to implement mentoring best practices and engage mentorship in a virtual environment.

The study directs attention to the psychological conditions experienced and knowledge management practices leveraged by faculty in higher education institutes (HEIs) to cope with the shift to emergency remote teaching caused by the COVID-19 pandemic. By focusing attention on faculty experiences during this transition, this study aims to examine an under-investigated effect of the pandemic in the Indian context.

Interpretative phenomenological analysis is used to analyze the data gathered in two waves through 40 in-depth interviews with 20 faculty members based in India over a year. The data were analyzed deductively using Kahn’s framework of engagement and robust coding protocols.

Eight subthemes across three psychological conditions (meaningfulness, availability and safety) were developed to discourse faculty experiences and challenges with emergency remote teaching related to their learning, identity, leveraged resources and support received from their employing educational institutes. The findings also present the coping strategies and knowledge management-related practices that the faculty used to adjust to each discussed challenge.

The study uses a longitudinal design and phenomenology as the analytical method, which offers a significant methodological contribution to the extant literature. Further, the study’s use of Kahn’s model to examine the faculty members’ transitions to emergency remote teaching in India offers novel insights into the COVID-19 pandemic’s effect on educational institutes in an under-investigated context.

Based on the theoretical predictions of media equation theory and the computers-are-social-actors (CASA) perspective, this study aims to examine the effects of performance error type (i.e. logical, semantic or syntactic), task type and personality presentation (i.e. dominant/submissive and/or friendly/unfriendly) on users’ level of trust in their personal digital assistant (PDA), Siri.

An experimental study of human–PDA interactions was performed with two types of tasks (social vs functional) randomly assigned to participants (N = 163). While interacting with Siri in 15 task inquiries, the participants recorded Siri’s answers for each inquiry and self-rated their trust in the PDA. The answers were coded and rated by the researchers for personality presentation and error type.

Logical errors were the most detrimental to user trust. Users’ trust of Siri was significantly higher after functional tasks compared to social tasks when the effects of general usage (e.g. proficiency, length and frequency of usage) were controlled for. The perception of a friendly personality from Siri had an opposite effect on social and functional tasks in the perceived reliability dimension of trust and increased intensity of the presented personality reduced perceived reliability in functional tasks.

The research findings contradict predictions from media equation theory and the CASA perspective while contributing to a theoretical refinement of machine errors and their impact on user trust.

Artificial intelligence (AI) technologies have led to significant transformations across industries and society, including the field of education. The integration of AI in educational settings has the potential to improve students' learning experience and support their individual competencies when paired with non-AI methods. Despite the growing importance of AI in modern education, there remains a noticeable research gap regarding its use in entrepreneurship education and the effects of Chatbots on students' entrepreneurial competencies. To address this gap, an exploratory study was conducted on undergraduate students who were tasked with using ChatGPT to improve their business model canvas.

The chosen methodology aligned with the research purpose, aiming to explore the relationship between Generative AI and competencies. Due to the novel nature of the research problem, an exploratory study was conducted using a mixed methods approach. A survey with open- and closed-ended questions was designed, and statistical and text analyses were performed to interpret data and test identified propositions.

The findings of this study indicate that ChatGPT can enhance the types of students' entrepreneurial competencies considered in this study: spotting opportunities, creativity, vision, valuing ideas and ethical and sustainable thinking. The results show that ChatGPT can be particularly helpful to improve the ability of students of valuing ideas.

Overall, this study highlights the potential of adopting ChatGPT in experiential learning methodologies for enhancing students' entrepreneurial competencies and improving their learning outcomes.