-confidence in their individualskills in oral communication, specifically related to presentations, but these results requireadditional research to confirm these findings.Using AI to Assess Student Outcomes: Co-Pilot and ChatGPT were both used to evaluate pitchtranscripts using the Grading Rubric. The results of AI-evaluations were compared to the facultyevaluations using the same grading rubric. This was limited to transcripts of the pitch as anyonline video-based platform for video analysis was by paid subscription only. In identifyingavailable AI tools, some interesting subscription-based options we discovered. These tools focusspecifically on video analysis of body language and pitch performance, including uSpeek(Sarang, 2023) and Bodha (Cadet
future role of generative AI in creativity and design, how you might utilize what you have learned in the course, and reflections on what you are learning in the course and the creative process. You should plan on writing at least a few paragraphs in this section every week.Figure 2. Descriptions for the sections that constitute the Foundational Creativity part of the Creativity Portfolio. Part 2: AI + Creativity Now is the time to use AI. For this section, please use your preferred generative AI tool (examples include Microsoft Copilot, Gemini, and ChatGPT) and write down which one(s) you used. Please record every prompt and output (yes, these sections will be long). Make sure your prompts are
, showcasing an enhanced ability to analyze and learn from failure. Table 4: Summary of ChatGPT comparison of pre-course and post-course responses to “How would you define a healthy mindset toward failure?” Pre- Post- Change Example Pre-Course Theme Course Course Example Post-Course Response (%) Response (%) (%) "By viewing it as a steppingstone to fully Focus on learning and understanding the content
in nano-makerspace, intellectual property strategy 4 Structured lab in nano-makerspace (I), case study with nanoscience entrepreneur (II) 5 Structured lab in nano-makerspace (II), team management, project idea brainstorming 6 Structured lab in nano-makerspace (III), computer-aided design 7 Project selection, identifying project value proposition and customer segment, project BMC check-in, identifying project prototype fabrication approach 8 Market landscape and customer relationships for project, library databases and ChatGPT 9 Storytelling, project BMC check-in, student-led
could focus on performing the jigsaw activities without thealumni present or the seminar series to see if the change in EM is similar and a larger sample sizeof students would benefit the study.AcknowledgmentsI would like to acknowledge the Robert D. and Patricia E. Kern Family Foundation, Inc. and thetask force of leaders representing the Engineering Unleashed Faculty Development communitywho selected me for the KEEN Fellowship and provided the grant funds for the activities.Additionally, I would like to thank Dr. Douglas Hacker who performed the statistical analysesreported within. During the preparation of this work, I used ChatGPT in order to improve thereadability and concision of the document. After using ChatGPT, I reviewed and edited
the Likert scale was computedfor each student with items 1, 3, 5, and 7 reverse-coded to produce a single Failure Mindsetassessment measure [8].We included all eight questions although previous studies omitted the health and vitality questions(questions 2 and 5) when applying to failure [4, 8]. We included these questions in the survey, butas detailed in the Discussion, we did not use these questions in the primary data analysis.In the end-of-semester survey, we also asked the students the following two open-endedquestions: 1. How would you define a healthy mindset toward failure? 2. How has this semester changed your Failure Mindset, positively or negatively?The responses were thematically grouped using ChatGPT, by supplying the full set
outputs from recently developed AI tools is a quite newchallenge that research communities are just now forming to address [23]. An investigation ofAI accuracy found that ChatGPT 3.5 proved, “…generally good at writing concepttopics…”[24]. One reasonably classifies a literature survey task as a concept topic, suggestingthe potential for accurate results from AI. However, this work uses Gemini 1.5 Flash, notChatGPT 3.5. Verhulsdonck and coauthors introduce a subjective means of evaluating theaccuracy of AI generated content independent of the particular tool [24]. Their HEAT method,an acronym formed from Human experience, Expertise, Accuracy and Trust, attempts tosubjectively gage AI output credibility. In this work’s contents, the H and E terms