Concept Of Learning Research Articles

How Do Teachers Perceive Lifelong Learning and Adult Education?

The objective of this study is to explore the perspectives of middle school teachers on the concepts of lifelong learning and adult education. The qualitative research involved 25 middle school teachers, and their responses, gathered through semi-structured interviews, underwent content analysis. Thematic analysis was employed to derive the results. The findings underscore that teachers attribute value to lifelong learning and adult education for various purposes, such as personal development, adaptation to evolving times, sustained learning, quality time utilization, social integration, and meeting educational needs. A consensus within the study group indicates that individuals across professions should engage in lifelong learning beyond their initial undergraduate education. The research reveals that continuous lifelong learning among teachers positively impacts performance, fostering open-mindedness, cultivating versatile thinking, facilitating effective lesson delivery, and improving interaction with students. Identified factors hindering lifelong learning include physical and economic conditions, environmental factors, health issues, motivation, and the repercussions of disasters. Additionally, teacher opinions shed light on shortcomings in lifelong learning and adult education within the Turkish context. Lastly, the study observes a general lack of adequate knowledge among teachers regarding global lifelong learning and adult education activities.

Learning stimulus for disengaged learners: Roles of outside participation

Background Learning contributes to adaptive performance needed in today’s business. A key challenge is workplace disengagement which can lead quiet quitting. Past studies indicate the compatibility when examining critical issues of learning in either a workplace or a classroom. Objective The case study examines the impacts on disengaged learners by outside participation. The business community’s participation focuses on providing continuous direct feedback and creating expectation (or subjective norms) at one upper secondary school where the feeling of disengagement has been prevalent. Methods The study’s construct adapts Theory of Planned Behavior and the Double-loop Learning Concept. The survey is completed by 171 current (Grade 12) and former students who have had two-year interactions with the business community from a group of 200 students. Statistical analysis is applied to examine the impacts on learning intention and behavior. Results The findings show the positive influence from direct feedback and subjective norms on intention to learn and attitude of disengaged learners which result in positive learning actions and behavior. Conclusions Dealing with disengagement should recognize consistency and continuity of feedback when involving outside participants. Feedback design to challenge the learners’ mindset and importance of subjective norm and informal learning are part of this consideration.

Embodied learning of science concepts through augmented reality technology

AbstractAugmented Reality (AR) revolutionizes educational approaches by providing an immersive experience that superimposes virtual 3D elements onto the physical environment. This integration of virtual and real worlds addresses the challenge of understanding abstract concepts by enabling three-dimensional visualization and interaction. This study aims to assess the role of embodied cognition in science learning through AR technology, analyze its impact on collaborative, inquiry-based learning in primary science, and understand students' perceptions of its influence on their engagement and comprehension in collaborative science tasks. Data collection methods for this study included three focus group interviews and five video observations involving ten grade 5 students, totaling 23 participants, in a primary science classroom. The analysis utilized content, thematic, and multimodal frameworks to evaluate student interactions. The findings indicated that the use of AR significantly enhanced the students' learning experiences. Students' comprehension of complex scientific concepts improved through active engagement with 3D models using the AR application. The AR app's 3D virtual shapes encouraged students to move around more during lessons, likely because these shapes were engaging and offered various perspectives. The use of embodied learning was enhanced with the support of AR technology, as students were constantly in motion around the table, using their fingers to manipulate objects and explore 3D forms from different angles.

Managing the tensions between tradition and innovation in family firms

PurposeThis study explores the relationship between innovation and tradition in family firms. By examining how these firms manage the potential tension between these two elements, the study aims to understand better how innovation and tradition coexist and support long-term survival across generations.Design/methodology/approachThis study has a constructivist standpoint and follows a qualitative methodology. By conducting a comparative case study, the data are collected from semi-structured interviews with 10 participants in 4 case companies located in Sweden. The data are analysed using thematic analysis.FindingsThis study found that managing the tension between innovation and tradition is carried out through four mechanisms: forward thinking through heritage, paradoxical thinking, operational control and governance. Moreover, the study further shows the great importance of the concept of intergenerational learning in family firms in managing tension.Originality/valueThe findings from this study contribute to the existing literature in family firms concerning managing tradition and innovation by providing a novel conceptualisation of the mechanisms embedded in this process. Moreover, the article proposes a grounded model, which could be used in research and practice when dealing with similar issues.

Sensemaking of wave–particle duality in a scientific outreach minicourse: a study based in self-regulation

Abstract On the Internet, Quantum Mechanics is an area of physics that is shrouded in misinterpretations. In this scenario, scientific outreach may serve as an instrument for disseminating scientific knowledge. Especially in this context, it is important that people’s learning encompasses more than the meanings of concepts and laws, involving aspects related to the ‘why’ and ‘for what purpose’ the knowledge was and is constructed. We consider these aspects as components of the sense, the connotative and subjective dimension of conceptual learning which encompasses a positioning of an individual towards a concept and its relevance in the physics framework. Motivated by this, in the present study, we investigated the senses ascribed to the concept of wave–particle duality (WPD) by 121 participants in a two-day (five-hour) science outreach minicourse in the double-slit experiment. Drawing on the ideas of Franco et al (2023, Cadernos de Pesquisa do Programa de Pós-graduação em Ensino de Física da UFRGS (Research Notebooks from the Postgraduate Program in Physics Teaching at UFRGS), Pimenta Cultural Editors S/A), we posit sensemaking as a type of cognitive effort to overcome a situation, viewed as a self-regulatory phenomenon wherein individuals self-observe, self-evaluate, and self-react to the situation to achieve a certain goal. In addition to identifying the senses attributed to the concept of WPD, we assessed the relationships between these senses and participants’ performance in a standardized test of this concept, as well as their educational background and field of study. Data were collected using questionnaires answered before and at the end of the course. The senses ascribed to the concept of WPD were investigated through similarity and cluster analysis based on responses to essay questions. The relationships among these senses, questionnaire performance, and educational background were evaluated using non-parametric statistical tests. We infer two senses attributed to wave–particle duality: (1) WPD is a basic and fundamental concept that impacts the way we comprehend the essence of nature, and (2) WPD is a very advanced concept restricted to the field of Quantum Mechanics. A statistically significant correlation (0.26 was identified between the senses attributed and participants’ performance on the standardized test, suggesting that the sense ascribed to a concept and performance in questions requiring its mobilization are overlapping elements but constitute two distinct dimensions of learning that need to be assessed simultaneously.

Time Efficient & Cost Effective Online teaching tool with iConcepts in Orthodontics for DDS students @ UoM

Background Traditional teaching methods in Orthodontics include plaster models and photos which have been used for decades, however due to the nature of being static still images its difficult for 3-Dimensional (3D) changes in Orthodontics teaching, which has posed immense challenges as the learner is unable to clear concepts on the different planes that affect the final tooth positions not to mention the protracted treatment time ranges from 12 months (simple cases) to 36 months (complex cases). In 2024 with variety of platforms such as videos, 3D animations, interactive changes in face and teeth can be added to teaching tools for Orthodontics. Furthermore, orthodontic movements can pose difficulty in understanding the changes particularly in growing children adding to the 4th dimension. At UQ (Naser-ud-Din, 2015) and internationally (Bridges, 2015) provided experience with creating online teaching modules highlighting its strengths of flexibility, ease of access on demand and global presence. UQ developed SBLi -Scenario Based Learning interactive for Postgraduate Orthodontic students who found it highly engaging, with self-reflective and self-assessment elements useful. (Khoo et al., 2023; Naser-ud-Din, 2016). Generally simulations can be expensive to create (Kröger et al., 2017) and it’s essential to explore cost effective simulation teaching tools with industry partners for authentic learning experience. Aims There is a gap in the dental education sector, particularly with emerging CADCAM (Computer Assisted Design and Computer Assisted Manufacture), which can be used to enhance the learning of core concepts in biomechanics with the aid of 3D simulated online learning. This is reflected particularly for the university students in undergraduate courses who need to feel confident and clinically ready on graduation as Dentists. Thus, greater expectations to be aligned with current technological processes in dentistry. Over the past 5 years, in particular, there has been exponential improvements by the industry providing 3D simulations for treatment planning and patient communication, commonly referred to as the GPS for smile transformations. The aim of this presentation is to highlight the time efficiency and cost effectiveness of the learning tool in sync with contemporary demands in Orthodontics to provide authentic learning platform that prepares the clinician for real patients. Material & Methods Currently the CAD CAM technology provide 3D simulations as open access to general public and doctors portal which can be utilized for teaching core concepts related to biomechanics foundations for student learning, engagement and self-assessment. This project envisages to create a novel forum encompassing education revolution as massive changes in delivery will occur with speed and efficiency internationally with onlinelearning demands. Hence, robust online presence with an interactive textbook such as iConcepts in Orthodontics under the banner of UoM to assist students in Doctor of Dental Surgery at MDS shall pave the way to learning needs for the future. Results The purpose of iConcepts a digital interactive online textbook is to create lifelong learning opportunities in safe space for visual, auditory and kinesthetic with quizzes for interactive learning of concepts without pressure in class learning and feeling judged by peers. Interactive 3D Orthodontic learning directly translates into clinical applications for various orthodontic cases. In the past decade CAD CAM has become clinically relevant particularly with Clear Aligner Therapy adding to higher precision and patient satisfaction. Moreover, it is imperative to have Long Term Retention (LTR) (Irvine, 2020) of learning new tasks. It is essential that students in dentistry are aware of the digital workflows and have clinical preparedness on graduation as it’s the future and certainly here to stay. Both qualitative and quantitative data on student experience shall be collected and analysed to seek out the best practices and processes for instruction of delivery in Orthodontics for DDS cohort in particular and lifelong learning for all ages in general encompassing time efficiency and cost effectiveness. Conclusion The current iConcepts is developed by the author with Apple Education and prototype is being assessed with MSc Data Science cohort at UoM. Furthermore, it is refined by Master of Science Software Engineering students at UoM. Future Recommendations Novel teaching tools shall be marketed to developing universities internationally assisting the dissemination of information a flagship for UoM and revenue generation for department of Education at UoM. In future there will be more and more demand towards interactive concepts clarification (Poblete et al., 2020) and self-assessments hence iConcepts provides that ideal platform. Such technologies will become more prevalent in the future particularly with AI and translated into different languages/ sectors of education. Various faculties that showcase start to finish particularly lengthy/complex outcomes can benefit with timelapse videos and 3D CADCAM for clarity and comprehension for the entire process such as patient journey throughout treatment in Orthodontics.

Enhancing Online Learning: Role Of Attention Detection Systems in Fostering Student Concentration

Online education is an inevitable trend. With just a smartphone, a tablet, or a personal computer, anyone, from teenagers to middle-aged individuals, from schoolchildren to workers, can access any free or paid courses in every aspect of society from economics, politics, literature, history, etc. foreign languages; Learners are free to choose lecturers, duration, time, space, and learning concepts as long as it suits their needs. However, online education still harbors many limitations, especially the issue of student distraction during online learning. This article elucidates the impact of online learning on student focus and analyzes the necessity of an attention detection system when studying online. Through surveys, the results indicated that up to 82.57% of students frequently lose focus when engaging in online learning, and 100% of opinions from education experts concur on the limitations of online learning. Based on these analyses, we provide insights into the necessity of developing and the crucial characteristics of an attention detection system to support learners in online education.

Examining students’ learning experiences in hybrid environments

In the aftermath of the pandemic, a generation of students who are comfortable with learning online and prefer having the autonomy to decide how they want to learn – in-person or remotely – has emerged. Hybrid learning, where teaching instruction is given to students in different spatial settings at the same time, is a modality that has the potential to deliver stimulating learning experiences to support diverse learning needs. The experiences in various forms of learning – in-person, fully online and hybrid – have exposed students to various modalities of learning and access to resources. However, the absence of physical presence and the lack of feedback from remote students has caused lecturers to be uncertain of the effectiveness of hybrid lectures and tutorials. Thus, understanding students’ learning and their considerations when determining their preferred modality will provide lecturers with clear strategies for supporting students. This qualitative study aims to examine students' learning experiences in a research-intensive public University in New Zealand university. The study was guided by the following questions: (i) What are students’ perceptions of learning in a hybrid environment?; and (ii) How do students learn in hybrid environments? In-depth interviews with 15 students who have experienced hybrid education in a research-intensive public university in New Zealand was conducted using a descriptive case study. Three categories that described students’ considerations and dispositions towards learning in hybrid environments, and how various conditions and resources within their learning environment influenced their behaviours emerged. Preliminary findings found that students’ dispositions towards learning were critical factors that contribute towards their behaviours in a hybrid environment. Unlike traditional conceptions of teaching and learning, hybrid education requires students to be active participants in their learning and take charge of their own learning in aspects such as deciding how they best learn. Despite minimal social and physical interaction with lecturers and their peers, students found hybrid learning to be effective. Interviews with students who had experienced hybrid education highlighted perspectives that differed from previous studies. Remote students showed willing and drive to excel in their studies despite being disconnected from their peers in the physical spaces, and did not feel that they had less of a learning experience. This finding echoes that of Zhong et al., where social presence was not found to be significantly related to learning persistence. Students found having immediate access to information and lecturers to be more important than whether they could communicate and interact with other in-person classmates. The study recommends strategies lecturers can employ to improve teaching practices in hybrid environments. This includes ensuring all materials are digitally captured synchronously and having a student partner to monitor questions or teaching assistant to address questions the chatroom will help remote students greatly. Further analysis of the current data will take a closer look at how students’ dispositions play a part in students’ engagement levels and their behaviours in hybrid environments.

The Effects of Social Cues in Self-Produced Micro Video Lectures on Parasocial Interaction, Motivational Interest, Extraneous Cognitive Load, and Concept Learning Performance: an Empirical Study in a Junior High School

Background and Aim: Videos are popular in the dissemination of knowledge at scale, which can be seen in various video-based platforms and educational disruption. However, inconsistent results were reported in studies. This research is designed to determine the effectiveness of social cues in self-produced micro video lectures on parasocial interaction, motivational interest, extraneous cognitive load, and concept learning performance and the relationship among them. Materials and Methods: Self-produced videos for learning concepts of morality and the rule of law in junior high schools were used as the treatment. Tests were used to determine concept learning performance and Likert scales were utilized to collect information on the other three variables. 248 students from the eighth grade in a public school were involved in the sample. One-way ANOVA was used to analyze differences among groups, and path analysis as well as was adopted to determine the relationship between variables. Results: There was no significant difference among the four groups on each variable. Parasocial interaction has a significant positive impact on motivational interest, motivational interest has a negative significant impact on extraneous cognitive load, and extraneous cognitive load has a negative significant impact on concept learning performance. Conclusion: The effects of the increment of types of social cues can be ignored in 6-minute self-produced video lectures. Students’ parasocial interaction can influence concept learning performance via the mediation of the cognition process and motivational factors. The extraneous cognitive load decreases with the stimulation of the motivational interest.

Factors Impacting Students’ Learning Performance in Higher Education in Chengdu, China

Background and Aim: The effectiveness of education has always been a focus of social attention. Previous research has mostly focused on the level of education in primary and secondary schools, and some studies have shown that college students may have different motivations and learning concepts. Therefore, this study aims to take Xihua University in Chengdu, China as an example to systematically examine various factors that affect the academic performance of university students. Through quantitative analysis, this study investigated the impact of five independent variables (learning attitude, learning anxiety, learning motivation, teacher ability, and student participation) on the dependent variable (academic performance), especially in higher education. Moreover, it aims to identify significant differences between variables. Methodology: Research Design, Data, and Methods: This study used the Project Objective Consistency Index (IOC) to test the validity of the questionnaire, and Cronbach's Alpha was used as reliability in the pilot study (n=30). They used the multiple linear regression method to analyze the effective responses of 80 students at Xihua University and verify the significant relationship between variables. Afterward, a group of 30 students underwent a 14-week planned study. Then, the quantitative results after and before the scheduled study were compared in paired sample t-tests. Results: In multiple linear regression, studies have shown that learning attitude, learning anxiety, learning motivation, teacher ability, and student participation have a significant impact on student academic performance. Finally, the comparison results of paired sample t-tests indicate substantial differences in student academic performance between the post-strategic and pre-strategic plan stages. Conclusion: This research endeavors to foster students' learning performance in the context of Chengdu, China.

Integrating ICAP theory in learning analytics

This paper introduces a conceptual evaluation learning analytics (LA) model developed by Keypath Education and Melbourne Business School to analyse student engagement in an online learning environment. The paper describes how a targeted LA intervention was grounded within the ICAP theory for active learning to identify, visualise and analyse student engagement metrics in a 100% online setting. The architecture of the model, including its design principles and underlying assumptions, are broadly examined against the latest research in educational, LA, and data analytics research. This includes a discussion of our initial phase testing results of captured student data alongside a discussion of key questions and desired study outcomes for the upcoming phase 2 of the data intervention. As a result, this paper provides both specific insights into how we created an evidence based and pedagogically sound evaluation model of online student engagement within a specific suite of asynchronous educational tools, as well as more general and practical insights into how other universities could develop similar approaches to enhance understanding and support of a growing online student population.

The Geometry and Dynamics of Meaning.

An enigma for human languages is that children learn to understand words in their mother tongue extremely fast. The cognitive sciences have not been able to fully understand the mechanisms behind this highly efficient learning process. In order to provide at least a partial answer to this problem, I have developed a cognitive model of the semantics of natural language in terms of conceptual spaces. I present a background to conceptual spaces and provide a brief summary of their main features, in particular how it handles learning of concepts. I then apply the model to give a geometric account of the semantics of different word classes. In particular, I propose a "single-domain hypotheses" for the semantics of all word classes except nouns. These hypotheses provide a partial answer to the enigma of how words are learned. Next, a dynamic cognitive model of events is introduced that replaces and extends the function of thematic roles. I apply it to analyze the meanings of different kinds of verbs. I argue that the model also explains some aspects of syntactic structure. In particular, I propose that a sentence typically refers to an event. Some further applications of conceptual spaces are briefly presented.

Application of machine learning algorithms in resource allocation for wireless communications

Abstract. The accelerated advances of wireless communication technologies in recent years has highlighted the necessity of efficient resource allocation in 5G and upcoming 6G networks, particularly in large-scale, high-density network implementations such as the Internet of Things (IoT) and ultra-dense cellular networks. The application of machine learning offers a number of significant advantages over traditional resource allocation algorithms, including enhanced adaptability, robustness, scalability, and predictive power. Therefore, the paper aims to examine the process of selecting the optimal machine learning algorithm for a specific resource management task. To this end, it provides an overview of the fundamental concepts of machine learning, including deep reinforcement learning (DRL), graph neural networks (GNN), and joint learning. Furthermore, this paper examines the potential applications of machine learning in the field of wireless resource management. The research presented in this paper provides a crucial theoretical foundation and guidance for further exploration and application of machine learning capabilities in the domain of wireless communication resource management. Overall, the research elucidates the potential of machine learning in wireless communication resource management and its applications, thereby advancing knowledge in this field and providing valuable references for the development of efficient and intelligent wireless communication networks.

Conceptual PlayWorlds: A transformational model for children’s learning and development in an early childhood education setting in Indonesia

Structured and teacher-directed play focused on children’s academic outcomes has proven problematic in Indonesian early childhood education. This contrasts with the PlayWorlds model, which emphasises both the primary activity of play and conceptual learning. However, there has been little research in Indonesia on the pedagogical aspects of the PlayWorlds model in creating conditions for children’s learning and development. The purpose of this study is to highlight the distinctive pedagogical and contextual aspects of Indonesian PlayWorlds by investigating how the implementation of the PlayWorlds model creates conditions for children’s learning and development. Using cultural-historical concepts to analyse the data, the findings reveal a transformational model of PlayWorlds that highlights five key elements: teachers’ role as play partners, the dialectical meaning-making process, degrees of freedom, motives and contradictions, and the unity of emotion and cognition. This model is shown to support pedagogical concepts and practices by providing opportunities for children’s development in play through the integration of imaginative, cognitive and affective skills. It is argued that the transformative paradigm of PlayWorlds as an innovative play pedagogy holds promise for children’s learning and development, while recognising play as their primary activity.

TreeQuestion: Assessing Conceptual Learning Outcomes with LLM-Generated Multiple-Choice Questions

The advances of generative AI have posed a challenge for using open-ended questions to assess conceptual learning outcomes, as it is increasingly common for students to use tools like ChatGPT to generate long textual answers. However, teachers still have to spend substantial time reading the answers and inferring students' learning outcomes. We present TreeQuestion, a human-in-the-loop system designed to help teachers create a set of multiple-choice questions to assess students' conceptual learning outcomes. When a teacher seeks to assess students' comprehension of specific concepts, TreeQuestion taps into the wealth of knowledge embedded within large language models and generates a set of multiple-choice questions organized in a tree-like structure. We evaluated TreeQuestion with 96 students and 10 teachers. Results indicated that students achieved similar performance in multiple-choice questions generated by TreeQuestion and open-ended questions graded by teachers. Meanwhile, TreeQuestion could reduce teachers' efforts in creating and grading the multiple-choice questions in contrast to manually generated open-ended questions. We estimate that in a hypothetical class with 20 students, using multiple-choice questions from TreeQuestion may require only 4.6% of the time compared to open-ended questions for assessing learning outcomes.

A review of multimodal deep learning methods for genomic-enabled prediction in plant breeding.

Deep learning methods have been applied when working to enhance the prediction accuracy of traditional statistical methods in the field of plant breeding. Although deep learning seems to be a promising approach for genomic prediction, it has proven to have some limitations, since its conventional methods fail to leverage all available information. Multimodal deep learning methods aim to improve the predictive power of their unimodal counterparts by introducing several modalities (sources) of input information. In this review, we introduce some theoretical basic concepts of multimodal deep learning and provide a list of the most widely used neural network architectures in deep learning, as well as the available strategies to fuse data from different modalities. We mention some of the available computational resources for the practical implementation of multimodal deep learning problems. We finally performed a review of applications of multimodal deep learning to genomic selection in plant breeding and other related fields. We present a meta-picture of the practical performance of multimodal deep learning methods to highlight how these tools can help address complex problems in the field of plant breeding. We discussed some relevant considerations that researchers should keep in mind when applying multimodal deep learning methods. Multimodal deep learning holds significant potential for various fields, including genomic selection. While multimodal deep learning displays enhanced prediction capabilities over unimodal deep learning and other machine learning methods, it demands more computational resources. Multimodal deep learning effectively captures intermodal interactions, especially when integrating data from different sources. To apply multimodal deep learning in genomic selection, suitable architectures and fusion strategies must be chosen. It is relevant to keep in mind that multimodal deep learning, like unimodal deep learning, is a powerful tool but should be carefully applied. Given its predictive edge over traditional methods, multimodal deep learning is valuable in addressing challenges in plant breeding and food security amid a growing global population.

Human Adaption to Climate Change: Marine Disaster Risk Reduction in the Era of Intelligence

With the intensification of global warming and sea level rise, extreme weather and climate events occur frequently, increasing the probability and destructive power of marine disasters. The purpose of this paper is to propose the specific application of artificial intelligence (AI) in marine disaster risk reduction. First, this paper uses computer vision to assess the vulnerability of the target and then uses CNN-LSTM to forecast tropical cyclones. Second, this paper proposes a social media communication mechanism based on deep learning and a psychological crisis intervention mechanism based on AIGC. In addition, the rescue response system based on an intelligent unmanned platform is also the focus of this research. Third, this paper also attempts to discuss disaster loss assessment and reconstruction based on machine learning and smart city concepts. After proposing specific application measures, this paper proposes three policy recommendations. The first one is improving legislation to break the technological trap of AI. The second one is promoting scientific and technological innovation to break through key technologies of AI. The third one is strengthening coordination and cooperation to build a disaster reduction system that integrates man and machine. The purpose of this paper is to reduce the risk of marine disasters by applying AI. Furthermore, we hope to provide scientific references for sustainability and human adaptation to climate change.

Virtual Digital Laboratory Vernier as a Tool of Implementing STEM-Education Principles in Physics Lessons

The article highlights the results of the theoretical and methodological analysis of the issue of the use of the Vernier digital virtual laboratory as an innovative tool for implementing the principles of STEM education in physics lessons in high school. The purpose of this research paper is to justify the feasibility of integrating digital laboratories into the physics curriculum, which allows for its modernization through the integration of science, technology, engineering and mathematics. The study's methodological foundation is based on the active learning concept developed by D. Sokoloff, R. Thornton and P. Laws. According to it, the active nature of learning physics using the Vernier digital laboratory is ensured by the ability to conduct real, high-precision, and multiple measurements of various physical quantities, analyze the obtained data, visualize them as graphs or charts, and interactively adjust and generalize the results of the experiment. The main advantages and disadvantages of using this innovative learning tool have been analyzed, and its compliance with safety, accessibility and adaptability requirements has been determined. The content of implementing the scientific, technological, engineering and mathematical aspects of STEM education through the methodology of using the Vernier digital laboratory in physics lessons has been explored. An example of a tentative lesson plan for a physics class using the Vernier digital laboratory is provided. Based on the conducted research and the practice of using the Vernier digital laboratory in middle school physics lessons, it has been concluded that it has significant and comprehensive educational potential as an innovative tool for implementing STEM education principles.

Learning super-resolution and pyramidal convolution residual network for vehicle re-identification

Vehicle re-identification (Vehicle Re-ID) aims at retrieving and tracking the specified target vehicle with multiple other cameras, which can provide help in checking violations and catching fugitives, but there are still the following problems that need to be solved urgently. First, the existing collected Vehicle Re-ID data often have low resolution and blur in local regions, so that the Vehicle Re-ID algorithm cannot accurately extract subtle feature representations. In addition, small features are easy to cause the disappearance of features under the operation of a large convolution kernel, which makes the model unable to capture and learn subtle features, resulting in inaccurate judgment of vehicles. In this study, we propose a Vehicle Re-ID method based on super resolution and pyramidal convolution residual network. Firstly, a super-resolution image generation network leveraging generative adversarial networks (GANs) is proposed. This network employs both content loss and adversarial loss as optimization criteria, ensuring an efficient transformation from a low-resolution image into a super-resolution counterpart, while meticulously preserving intricate high-frequency details. Then, multi levels of pyramidal convolution operations are designed to generate multi-scale features, which can capture information on different scales. Moreover, the concept of residual learning is applied between the multi levels of pyramidal convolution operations to expedite model optimization and enhance recognition capabilities. Ultimately, the double pyramidal convolutions are meticulously employed on both the original image and the super-resolution image, yielding low-noise feature representations and intricate semantic information respectively. By seamlessly fusing these two diverse sources of information, the resultant combined features exhibit heightened discrimination capabilities and significantly bolster the robustness of image features. In order to verify the effectiveness of the proposed method, extensive experiments are carried out on VeRi-776 and VehicleID datasets. The experimental results show that the method proposed in this paper effectively captures the detail information of vehicle images, accurately distinguishes the subtle differences between different vehicles of the same type, and is superior to state-of-the-art methods.

Considering the relevance of Jiddu Krishnamurti to contemporary Indian education: In conversation with the thought of Gert Biesta

Education was a compelling symbol in India’s struggle for independence representing as it did, empowerment, transformation, and liberation. India’s contemporary education system, influenced by neoliberalism has, however, largely focused on curricula, skills, literacy, and educational attainment, while overlooking the concepts of freedom or humanisation advocated by Indian educational philosophers. This article places pre-eminent philosopher of education, Gert Biesta, in conversation with Indian thinker, Jiddu Krishnamurti. The focus of this exchange is to consider, from the perspective of Biesta, the aims and conceptions of education, as proposed by Krishnamurti. Krishnamurti strongly emphasised the importance of a learner-centred approach that would cultivate critical thinking, enable learners to gain a deeper understanding of the integrated processes of life, and provide them an environment for realising their full human potential. The aim of Krishnamurti’s education philosophy was to empower the individual to be free, and capable of dealing with life as a whole, based on the conception of collaborative learning, self-awareness, moral virtues and the ability to live well. Though he acknowledges the importance of technique, curricula, and attainment, Biesta’s approach emphasises that students are not objects who need to be trained. Rather, their development as people with the discernment to know when to act and when to refrain from acting, is a critical function of education. Through its examination of the perspectives of Krishnamurti, from the contemporary standpoint of Biesta’s articulation of the purposes of education, this article argues for the relevance of Krishnamurti’s educational philosophy in India’s current educational realities.