European, Black or African, Hispanic or Latino, Middle Eastern or North African, Asian, Native American, Slavic, or I prefer not to say. • Technical_Talent: Assessed technical skills. Range: Terrible (1) to Wonderful (5). • Learning_Process: Learning style. Range: Visual, Auditory, Reading/Writing, or Kinesthetic. • Learning_Approach: Learning method. Range: Collaborative, Experiential, or Observation. • Early_Adapter: Whether the student tends to adopt new technologies early. Range: Yes or No.The target variable, Test_Group, categorizes students into those who review with AI, review withthe internet, review with a peer, contemplate on their own, or choose any method they like.We then asked a set of 10 to 12
courses in data security, cryptography, computer forensics, and senior project writing. Her research interests include machine learning, artificial intelligence, cryptography, steganography, and security. Arzu focuses on providing hands-on learning experiences and integrating real-world applications into her curriculum, ensuring her students gain the skills needed for successful careers in technology and security fields. ©American Society for Engineering Education, 2024 Integrate the iPad, Apple Pencil, and Goodnotes, to enhance teaching effectiveness.AbstractUsing multimedia such as slides, diagrams, charts, and videos as visual aids during lectures hasproved
-institution) funded program built on the theoretical framework oflegitimate peripheral participation [3] with an emphasis on inclusivity, community, and belonging[4]. To date, the Program has increased Scholar retention, academic performance, and engagementwith student support services relative to peers [5].As part of the Program, an annual faculty workshop was designed to catalyze and sustaincollaborations between NCC and HU STEM faculty. The workshop consisted of interactivemodules to facilitate directed discussions and produce deliverables. We will share the lessonslearned, obstacles overcome, and the outcomes of the collaborative process of hosting this type ofworkshop. The paper documents the process used to identify workshop outcomes and
to prevent plagiarism and copyright infringementwhile promoting responsible use of AI tools to uphold academic integrity 27, 28. The proliferationof AI-generated contents and automated writing assistance tools presents new challenges for main-taining academic standards and preserving the originality of student work. Educators should pro-vide students with clear guidelines and training on ethical writing practices, citation conventions,and the proper use of AI tools to support their learning while ensuring academic integrity 29. Ad-ditionally, institutions should invest in plagiarism detection technologies and educational re-sources to help students understand the importance of academic honesty and the consequences ofintellectual property