Learning and Motivation最新文献

The “be creative” instruction has been reported to improve individuals’ creativity. However, this “be creative” effect has seldom been examined alone in a synthesis study. This study bridged this gap in the literature and conducted a meta-analysis that examines the “be creative” effect on different dimensions of creativity, using the quality and/or quantity of creative solutions, the focus of the instruction, and control group instructions as the moderators. Results showed that the “be creative” instruction had a moderate effect on creativity (d =.69, p < 0.001) and a significant effect on originality (d =.79, p < 0.001) but no effect on fluency (d =.06, p > 0.1) or flexibility (d =.48, p > 0.1) of the products. Meta-regression analyses revealed the specific roles of the moderators in different situations. Implications of these results for educational settings are considered.

Errorless learning is a stimulus fading procedure that can reduce incorrect responses in a stimulus discrimination task. Errorless learning has been described as a beneficial dog training procedure, although minimal research has been performed with dogs to support its use. The current study compared the effects of using an errorless learning to a trial-and-error learning procedure to train a stimulus discrimination in companion dogs. Eight dogs were trained, four in each group, with concurrent stimuli and either through gradually fading in an incorrect stimulus (errorless learning group) or by differentially reinforcing correct and incorrect responses (trial and error group). Correct responses, incorrect responses, frustration-related responses, and non-responses were measured and compared across the two groups. The results showed the errorless learning dogs were more likely to meet the criteria for learning the discrimination, showed faster speeds of acquisition, and displayed fewer frustration-related behaviours compared to the trial-and-error group. These results are discussed in relation to their benefits for training dogs more effectively and with better welfare during training, suggesting errorless learning could be more greatly utilized for canine training and research.

In traditional learning contexts, teachers primarily assess students' behavior, emotional changes, and assignment completion to ensure teaching quality. Currently, there are challenges in evaluating students, such as assessments being insufficiently comprehensive and timely, a singular evaluation perspective that hinders the holistic consideration of factors affecting learning assessments, and a weak correlation among evaluation criteria, resulting in suboptimal evaluation outcomes. In recent years, with the rapid development and widespread application of artificial intelligence and information technology, the era of smart classrooms has arrived. New technologies like image processing and artificial intelligence offer opportunities for personalized support services and enhancing teaching quality. Therefore, to provide a more comprehensive and objective reflection of teaching quality, this paper proposes a multi-modal information fusion learning assessment model. This model is achieved by determining the weight values of three dimensions, cognitive attention, emotional attitude, and course acceptance along with their corresponding attributes. Subsequently, through a fusion strategy, it calculates the learning assessment score by integrating information from these three dimensions. A series of experimental data confirms the effectiveness of this approach.

Currently, some problems still exist in the cultivation system of innovative and entrepreneurial talents. Therefore, the education department should also continue to carry out practice on the relevant talent training mode, to determine the talent training mode most suitable for the growth of polytechnic colleges. Colleges and universities should take entrepreneurship and innovation ability as the fundamental purpose so that students are not only job seekers, but also creators. The fuzzy set and its extended modelling are crucial for developing students' innovation skills. Therefore, on this basis, this paper proposed a model for cultivating innovative talents with fuzzy sets as the core. The fuzzy comprehensive evaluation (FCE) method is one of the most widely utilized and efficient evaluation methods, which applies to multi-objective evaluation models, thus reflecting the comprehensive and complex nature of the assessment. The ultimate purpose was to derive the decision rules and help the decision-makers make better decisions. The experimental findings of this article showed that there were 3 and 4 students with strong practical ability in Model 1 and Model 2 before the experiment, and there were 8 and 33 students with strong practical ability in Model 1 and Model 2 after the experiment.

Using data from the Wabash National Study of Liberal Arts Education, we analyzed whether certain precollege characteristics and experiences predicted students’ academic motivation when entering their first year of college. Results indicated that some precollege experiences positively predicted students’ academic motivation at the start of college, including certain minoritized identities, such as holding non-U.S. citizenship status, being a first-generation student, and being low-income; as well as higher measures of academic achievement and engagement, such as a higher high school GPA, a higher frequency of participation in high school extracurriculars, and a higher frequency of interacting with teachers. Conversely, higher ACT/SAT scores and higher reported frequency of socializing with friends negatively predicted students’ precollege levels of academic motivation. Implications for institutions of higher education, including faculty staff, as well as for high school guidance counselors, are considered.

With the increased request for better student success, several methods investigate teachers' effectiveness undertaken with continued support from a related learning technology. With less durational experiences or extended education, programmers can have several ranges in theory-based universities. Teaching effectiveness in higher education strengthens students' impact and performance in the learning environment. The technological development in different platforms is completely understood and enhances education strategies. Community-based learning advantages for higher education are well recorded. The author concludes that educational institutions must make thoughtful choices about the parts they use, that they should strategically manage the network of internal and external stakeholders, including all communications and well-informed decisions, that they should recognize that shifts in student perceptions are common and encourage flexibility in system operations, and that it is normal for platforms to have specialized, high-performing departments/sections. The perspective of the group member is relatively less understood. Therefore, this paper proposes a community theory-based learning (CT-BL) framework to improve higher education learning technologies. CT-BL presents perspectives on how professors should contribute to strengthening partnerships between students and educators. The descriptive statistical model is used in a questionnaire session to recognize the central points in community participants' answers. Practical application of the framework within a variety of conservation groups illustrates the integrated approach's potential to serve as a portal through which practitioners can enter the realm of social science theory to better comprehend the current state and future directions of CT-BL interventions and activities. Students from several universities form collaborations to describe the way of theory-based learning. The community-based learning is evaluated based on the questionnaire raised by the learning participants. The community-based theory enhances higher education learning technologies. The overall participants of the University's higher education strategies are focused on community-based learning. Added teacher support for student awareness of information, experience, and competence and expanded academic participation in all cooperation elements involving advisor suggestions. The numerical results show that the proposed CT-BL model enhances the evaluation rate of 95.6%, reliability ratio of 94.2%, an efficiency ratio of 95.3%, the recognition accuracy of 90.3%, learning recognition rate of 92.2%, the impact of beliefs of 96.2%, dynamic nature rate of 93.4% when compared to other existing models.

This research study investigates the effects of jigsaw cooperative learning (JCL) on academic motivation (AM), academic hardiness (AH), and self-efficacy (SE) of English as a Foreign Language (EFL) learners. JCL is an educational strategy that emphasizes collaboration, interdependence, and group cooperation. However, limited research has examined the specific impact of JCL on these factors among EFL learners. Thirty-eight learners from each of the two groups—one was the experimental group (EG) and the other was the control group (CG)—were randomly chosen from among the learners who had been chosen in the academic year 2023. Data were collected using three questionnaires on AM, AH, and SE. Before implementing the JCL treatment, both groups completed the questionnaires as a pretest. A post-test was administered after teaching JCL in the EG and using the traditional method in the CG. Descriptive and inferential statistics, including covariance tests, were conducted to analyze the collected data. The outcomes showed that JCL, as a cooperative learning technique, improved students' AM, AH, and SE. A comparison of the pretest and post-test results confirmed the significant and positive influence of JCL on AM, AH, and SE. These results suggest that the application of JCL techniques can facilitate the development of AM, AH, and SE among EFL learners. These findings have implications for EFL instructors and practitioners, as they can utilize JCL strategies to enhance their learners’ AM, AH, and SE in the classroom.

Computer Vision-based English translation approaches pledge robots to master complicated functions. Conversely, the debate remains unanswered as to how to extend persuasion skills to real-world relationships. The stable operation of robots in English translation is an upcoming development in the educational field. The development of science and technology in the form of robots helps in computer vision technology for object detection and learning. In education, the usage of advanced technology is still facing challenges in English translation based on the computer vision of robots. In the article, researchers investigate robotic simulation, movement identification, and target tracking in computer vision, learning from one illustration of the third person's perspective. Researchers consider using a previous information basis like a text repository to deduce the feature to be dealt with as part of a robot to promote its generalization through object detection and learning. A Robot translation based on computer vision of English translation (RT-CV) framework is proposed in the research. Robots' word recognition, facial expression, speech, and movement are captured and based on computer vision; the translation is permitted with the basic functions. RT-CV is implemented in real-world applications with manipulative functions with generalized outcomes. The results are obtained as emotional interaction with robots’ ratio is 87.6%, improving computer vision ratio is 88.7%, the Estimation of translating speed ratio is 84.5%, the efficiency of English translation ratio is 93.8%, and anxiety reduction through communication ratio is 82.2%.

The literature addresses the importance of developing competencies, but not from the complexity theory, nor does it show the importance of the correlation between gender and age in this process. This article aims to show the results of a study seeking a possible correlation between the perceived achievement of complex thinking competency and gender and age in a student population attending a technological university in western Mexico. The intention is to argue whether there is a statistically significant difference in the acquisition and development of this competency between men and women of different ages during their training. Methodologically, a multivariate descriptive statistical analysis was carried out to demonstrate the relationship between these indicators. We concluded that there is evidence of a gender gap in developing the perceived achievement of the complex thinking competency and its sub-competencies since neither in the overall result nor in the specific results by indicator did women achieve results proportional to those of their male peers, although, in most competencies, they initially surpassed them. The learning experience shows that the gender gap in perceived achievement of complex thinking competency widens as the student population advances in their training process.

Which learning processes best support revision of educationally-relevant misconceptions in college students? In this study, we investigated the generative process self-derivation through memory integration, the integration of multiple facts to generate novel, never-directly-taught information. Specifically, we examined whether self-deriving correct information supported revision of misconceptions above and beyond an active, yet non-generative, learning process: rephrasing directly-provided correct information. We found that misconception revision occurred across both conditions, but at higher rates in the rephrase condition. However, the two learning processes led to equal success in revising misconceptions when only correct, generative self-derivation trials were considered. Thus, correctly generating one’s own information was critical for success in the self-derivation condition. These findings contribute to our understanding of generative learning processes such as self-derivation. The results also offer insight into scaffolding misconception revision, particularly highlighting the benefit of directly exposing learners to corrective information.