Freedom to Learn and Freedom to Teach in Science Learning through ChatGPT: Systematic Literature Review

Education is very important in preparing people to be able to maintain and improve the quality of life as individuals with dignity. The severity of the challenges faced in all fields can be seen from various kinds of reports such as student learning outcomes, the inability of the community to keep their children successful in educational institutions up to the age of compulsory education. The evaluation system, education management and what is most often highlighted by the mass media today is the problem of the concept of Freedom to Learn and Freedom to Teach in Science Learning through ChatGPT. The purpose of this study is to examine Freedom to Learn and Freedom to Teach in Science Learning. A review is conducted on the state-of-the-art methods using the preferred reporting items for reviews and meta-analyses (PRISMA) guidelines. The results of this study can be seen from the aspects of affective learning and teaching models, learning methods, and self-learning methods sharing for information can facilitate the learning process in the independent curriculum, using the help of ChatGPT technology which functions to provide easiness in the process of achieving education. As part of modern technological innovation, ChatGPT has an impact on the world of education. Schools, teachers, and students can benefit from this artificial intelligence technology. ChatGPT can be a useful learning partner in implementing the Independent Curriculum

Direct and Constructivist Instructional Design: A Comparison of Efficiency Using Mental Workload and Task Performance

This paper investigates the efficiency of two instructional design conditions: a traditional design based on the direct instruction approach to learning and its extension with a collaborative activity based upon the community of inquiry approach to learning. This activity was built upon a set of textual trigger questions to elicit cognitive abilities and support knowledge formation. A total of 115 students participated in the experiments and a number of third-level computer science classes where divided in two groups. A control group of learners received the former instructional design while an experimental group also received the latter design. Subsequently, learners of each group individually answered a multiple-choice questionnaire, from which a performance measure was extracted for the evaluation of the acquired factual, conceptual and procedural knowledge. Two measures of mental workload were acquired through self-reporting questionnaires: one unidimensional and one multidimensional. These, in conjunction with the performance measure, contributed to the definition of a measure of efficiency. Evidence showed the positive impact of the added collaborative activity on efficiency

Training self-regulated learning skills with video modeling examples: Do task-selection skills transfer?

Self-assessment and task-selection skills are crucial in self-regulated learning situations in which students can choose their own tasks. Prior research suggested that training with video modeling examples, in which another person (the model) demonstrates and explains the cyclical process of problem-solving task performance, self-assessment, and task-selection, is effective for improving adolescents’ problem-solving posttest performance after self-regulated learning. In these examples, the models used a specific task-selection algorithm in which perceived mental effort and self-assessed performance scores were combined to determine the complexity and support level of the next task, selected from a task database. In the present study we aimed to replicate prior findings and to investigate whether transfer of task-selection skills would be facilitated even more by a more general, heuristic task-selection training than the task-specific algorithm. Transfer of task-selection skills was assessed by having students select a new task in another domain for a fictitious peer student. Results showed that both heuristic and algorithmic training of self-assessment and task-selection skills improved problem-solving posttest performance after a self-regulated learning phase, as well as transfer of task-selection skills. Heurist

How a growth mindset can change the climate: The power of implicit beliefs in influencing people's view and action

Although people seem to be concerned about climate change, few are pro-actively engaged in attempting to mitigate it. This discrepancy between environmental view and action has been recognized as a great challenge. This empirical study examined that disparity by investigating people's mindsets about the world. Such mindsets concern the degree to which people perceive their world as

The Evolution of Cognitive Load Theory and the Measurement of Its Intrinsic, Extraneous and Germane Loads: A Review

Cognitive Load Theory has been conceived for supporting instructional design through the use of the construct of cognitive load. This is believed to be built upon three types of load: intrinsic, extraneous and germane. Although Cognitive Load Theory and its assumptions are clear and well-known, its three types of load have been going through a continuous investigation and re-definition. Additionally, it is still not clear whether these are independent and can be added to each other towards an overall measure of load. The purpose of this research is to inform the reader about the theoretical evolution of Cognitive Load Theory as well as the measurement techniques and measures emerged for its cognitive load types. It also synthesises the main critiques of scholars and the scientific value of the theory from a rationalist and structuralist perspective

An Evolutionary Upgrade of Cognitive Load Theory: Using the Human Motor System and Collaboration to Support the Learning of Complex Cognitive Tasks

Cognitive load theory is intended to provide instructional strategies derived from experimental, cognitive load effects. Each effect is based on our knowledge of human cognitive architecture, primarily the limited capacity and duration of a human working memory. These limitations are ameliorated by changes in long-term memory associated with learning. Initially, cognitive load theory's view of human cognitive architecture was assumed to apply to all categories of information. Based on Geary's (Educational Psychologist 43, 179-195 2008; 2011) evolutionary account of educational psychology, this interpretation of human cognitive architecture requires amendment. Working memory limitations may be critical only when acquiring novel information based on culturally important knowledge that we have not specifically evolved to acquire. Cultural knowledge is known as biologically secondary information. Working memory limitations may have reduced significance when acquiring novel

Training self-regulated learning skills with video modeling examples: Do task-selection skills transfer?

Self-assessment and task-selection skills are crucial in self-regulated learning situations in which students can choose their own tasks. Prior research suggested that training with video modeling examples, in which another person (the model) demonstrates and explains the cyclical process of problem-solving task performance, self-assessment, and task-selection, is effective for improving adolescents’ problem-solving posttest performance after self-regulated learning. In these examples, the models used a specific taskselection algorithm in which perceived mental effort and self-assessed performance scores were combined to determine the complexity and support level of the next task, selected from a task database. In the present study we aimed to replicate prior findings and to investigate whether transfer of task-selection skills would be facilitated even more by a more general, heuristic task-selection training than the task-specific algorithm. Transfer of task-selection skills was assessed by having students select a new task in another domain for a fictitious peer student. Results showed that both heuristic and algorithmic training of self-assessment and task-selection skills improved problem-solving posttest performance after a self-regulated learning phase, as well as transfer of task-selection skills. Heuristic training was not more effective for transfer than algorithmic training. These findings show that example-based self-assessment and task-selection training can be an effective and relatively easy to implement method for improving students’ self-regulated learning outcomes. Importantly, our data suggest that the effect on task-selection skills may transfer beyond the trained tasks, although future research should establish whether this also applies when trained students perform novel tasks themselves