Search

This paper examines the potential benefits and challenges of using the generative AI model, ChatGPT, in higher education, in the backdrop of the constructivist theory of learning. This perspective-type study presents five benefits of ChatGPT: the potential to facilitate adaptive learning, provide personalised feedback, support research and data analysis, offer automated administrative services, and aid in developing innovative assessments. Additionally, the paper identifies five challenges: academic integrity concerns, reliability issues, inability to evaluate and reinforce graduate skill sets, limitations in assessing learning outcomes, and potential biases and falsified information in information processing. The paper argues that tertiary educators and students must exercise caution when using ChatGPT for academic purposes to ensure its ethical, reliable, and effective use. To achieve this, the paper proposes various propositions, such as prioritising education on the responsible and ethical use of ChatGPT, devising new assessment strategies, addressing bias and falsified information, and including AI literacy as part of graduate skills. By balancing the potential benefits and challenges, ChatGPT can enhance students’ learning experiences in higher education.

Universities increasingly expect students to publish during a PhD candidature because it benefits the candidate, supervisor, institution, and wider community. Here, we describe a method successfully used by early-career researchers including PhD candidates to undertake and publish literature reviews – a challenge for researchers new to a field. Our method allows researchers new to a field to systematically analyse existing academic literature to produce a structured quantitative summary of the field. This method is a more straightforward and systematic approach than the traditional ‘narrative method’ common to many student theses. When published, this type of review can also complement existing narrative reviews produced by experts in a field by quantitatively assessing the literature, including identifying research gaps. The method can also be used as the initial step for further analysis, including identifying suitable datasets for meta-analysis. Students report that the method is enabling and rewarding.

This study aimed to investigate: 1) the influence of 4C learning model on students' learning outcomes in the philosophy of science course, 2) the influence of academic capability on students' learning outcomes in the philosophy of science course, and 3) the interaction between 4C learning model and academic capability on the students' learning outcomes in the philosophy of science course, in cognitive, psychomotor, and affective domains at UIN Walisongo Semarang academic year of 2019/2020. This study was a quasi-experimental research with 2x3 factorial design. The study was conducted at UIN Walisongo Semarang academic year of 2019/2020 on the first years students of Islamic Communication Department. Techniques in collecting the data were multiple choise tests, essay tests, observations, and documentation. The hypothesis testing used two-way ANOVA test with a significance level of 5%. The result of it related to the influence of 4C model on the students' learning outcomes had showed the significance values in cognitive, psychomotor, and affective domains. The value of cognitive domain was 0.314, the value of psychomotor domain was 0.032, and the value of affective domain was 0.038. The result of hypothesis testing used two-way ANOVA test related to the influence of academic capability on the students' learning outcomes had showed the the significance values in cognitive, psychomotor, and affective domains. It was suggested to implement 4C learning model that would influence the students' learning outcomes.

Health care is evolving and with it the need to reform medical education. As the practice of medicine enters the age of artificial intelligence (AI), the use of data to improve clinical decision making will grow, pushing the need for skillful medicine-machine interaction. As the rate of medical knowledge grows, technologies such as AI are needed to enable health care professionals to effectively use this knowledge to practice medicine. Medical professionals need to be adequately trained in this new technology, its advantages to improve cost, quality, and access to health care, and its shortfalls such as transparency and liability. AI needs to be seamlessly integrated across different aspects of the curriculum. In this paper, we have addressed the state of medical education at present and have recommended a framework on how to evolve the medical education curriculum to include AI.

" of students and graduates is a demonstration of its role as sustaining the person, the expert/professional, and the citizen. This role has persisted in the face of rising global challenges such as the emergence of new learning spaces, the growing diversity of publics, the call for productivity and performativity, and the hope for a significant engagement with the community and the public good. These sometimes conflicting tendencies have also stimulated higher education institutions to further pedagogical strategies that articulate in novel ways the classical elements of learning: action/experience and reflection/theory. In this context, service learning received a new impetus, particularly in the post-Bologna European Higher Education Area, as universities were looking for ways in which to articulate the social dimension of HEI and their "third mission" as institutions not only committed to addressing and solving societal problems, but also committed to fostering public-minded alumni through powerful experiences of engagement for both the students and the community. This paper is based on the experience of Erasmus+project ESSA, a service earning based project focused on University social responsibility (USR). ESSA engaged four groups of students from three European universities (Edinburgh, Porto, and Kaunas) in conducting a 1-week on-site USR audit based on an ecologic and situated concept of social responsibility. We will consider the perceived impact of ESSA on 44 students through a thematic analysis of focus group discussions and student self-assessment reports produced during and after their participation in the USR audit.

Student satisfaction has become an important concept in higher education because students are paying higher tuition fees and increasingly seeing themselves as customers and because satisfaction is commonly used as an indicator of quality by quality assurance agencies and the compilers of rankings and league tables. In business organisations, it has been established that employee commitment has a significant impact on employee performance and customer satisfaction. The purpose of this research is to examine the effects of lecturer commitment on student perceptions of teaching quality and student satisfaction. The sample comprised 24 lecturers and 456 students at one Chinese university. Data were obtained through self-administered paper-based questionnaires. A model linking lecturer commitment with students’ perceived teaching quality and student satisfaction was created and the hypotheses were tested using structural equation modelling. It was found that lecturer commitment to students’ academic achievement and lecturer commitment to the social integration of students are both positively related to student satisfaction. However, lecturer commitment to the social integration of students did not appear to influence students’ perceptions of teaching quality. The implications for higher education institutions are discussed.

What Is The Field Of Social Justice About?Social psychologists have a long history of interest in the basis of people's cognitions, attitudes and behaviors in social interactions.Why does a concern about people's feelings and actions in social settings lead social psychologists to study social justice?Studies show that judgments about what is "just", "fair", "deserved", or something one is "entitled" to receive are a central social judgment which lies at the heart of people's feelings, attitudes, and behaviors in their interactions with others.Perceptions of injustice are closely related to feelings of anger (Montada, 1994; Shaver et al, 1989) and envy (Smith, Parolt, Ozer and Moniz, 1994), to psychological depression (Hafer and Olson, 1992;Walker and Mann, 1987) and to moral outrage (Montada, 1994).Further, judgments of fairness are significantly related to people's interpersonal perceptions (Lerner, 1981), political attitudes (Tyler, 1990;Tyler, Rasinski and McGraw, 1985) and prejudice toward outgroups (Lipkus and Siegler, 1993; Pettigrew and Meertons, 1994).People's actual behavior is also strongly linked to views about justice and injustice.A wide variety of studies link justice judgments to positive behaviors such as willingness to accept third-party decisions (Tyler, 1990); willingness to help the group (Moorman, 1991;Organ and Moorman, 1993); and willingness to empower group authorities (Tyler and Degoey, 1994).Conversely, other studies link the lack of justice to sabotage, theft, and on a collective level, to the willingness to rebel or protest (Greenberg, 1990;Moore, 1978;Muller and Jukam, 1983).In other words, how people feel and behave in social settings is strongly shaped by judgments about justice and injustice. 1Such justice judgments are of special interest to social psychologists because justice standards are a socially created reality.They have no external referent of the type associated with physical objects.Instead, they are created and maintained by individuals, groups, organizations, and societies.In addition to being important because it addresses central social psychological questions, social justice is important because its predictions are counterintuitive, and contrary to the prevailing selfinterest models which dominate the social sciences.Since the "rational" view of the person that currently informs and influences much of social science and public policy assumes that people are motivated by self interest, not by concerns about justice, departures from this rationality are both theoretically and socially important.Social justice research shows that people's feelings and beliefs are not consistent with the feelings that would be predicted by self-interest theories.A self-interest model predicts that those who receive more compensation for their work will be more satisfied.However, this prediction is not borne out by the data.Instead, people's satisfaction is linked to whether or not they feel that they are receiving fair compensation.Those receiving fair compensation indicate greater satisfaction than those receiving higher, but unfair, levels of compensation (Walster, Walster, and Berscheid, 1978).Social justice research on behavior also reflects departures from a self-interest or rational choice model.For example, people are willing to punish others who act unfairly even at a personal cost to themselves.Further, in situations of unequal power, social exchange theory predicts that people with greater power will use their power to achieve unequal gains.Research suggests that they do, but that their behavior does not fully exploit their power advantages (Guth, Schmittberger, Schwarze, 1982;Ochs and Roth, 1989).Instead, their behavior seems to reflect a concern for fairness.The failure of advantaged people not to fully press their resource and power advantages is consistent with the suggestion that people care about justice (Smith and Tyler, in press). The Field Of Social JusticeResearch on social justice generally addresses itself to six questions.The first is whether judgments about justice and injustice shape people's feelings and attitudes.The most clear cut evidence for the importance of justice concerns comes from investigations of what people think and feel.When people are asked to indicate their subjective reactions to their outcomes, for example satisfaction or