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Ai-Supported Academic Advising: Exploring Chatgpt’S Current State And Future Potential Toward Student Empowerment, Daisuke Akiba, Michelle C. Fraboni
Ai-Supported Academic Advising: Exploring Chatgpt’S Current State And Future Potential Toward Student Empowerment, Daisuke Akiba, Michelle C. Fraboni
Publications and Research
Artificial intelligence (AI), once a phenomenon primarily in the world of science fiction, has evolved rapidly in recent years, steadily infiltrating into our daily lives. ChatGPT, a freely accessible AI-powered large language model designed to generate human-like text responses to users, has been utilized in several areas, such as the healthcare industry, to facilitate interactive dissemination of information and decision-making. Academic advising has been essential in promoting success among university students, particularly those from disadvantaged backgrounds. Unfortunately, however, student advising has been marred with problems, with the availability and accessibility of adequate advising being among the hurdles. The current study …
Preliminary Efficacy Of Motivational Interviewing On Problem Drinkers 55 And Older Compared To Younger Counterparts, Alexis Kuerbis, Sijing Shao, Nehal Vadhan, Jon Morgenstern
Preliminary Efficacy Of Motivational Interviewing On Problem Drinkers 55 And Older Compared To Younger Counterparts, Alexis Kuerbis, Sijing Shao, Nehal Vadhan, Jon Morgenstern
Publications and Research
Background: Older adults who drink problematically are the largest group of substance users among those 55 and older. This group often chooses moderation as a goal instead of abstinence, and motivation and self-efficacy are found to have less of an impact on drinking compared to younger adults. No study has examined age effects (specifically 55 and older vs. younger counterparts) on motivational interviewing (MI) compared to brief advice with a sample that includes individuals over 65. Objective: To explore the moderating impact of age on heavy drinkers’ (aged M=50.7 years SD=11.6, range 23-73) response to MI. Methods: Data …