Learning Phenomena Research Articles

“You’re not learning skills—you’re just realizing what you can do”: a preliminary study of self-regulation in higher education

IntroductionThis preliminary study employs a phenomenological approach to investigate the phenomenon of self-regulated learning among higher education students in the United Kingdom. The research seeks to identify both facilitators and challenges associated with effective self-regulated learning, shedding light on the factors that influence students’ ability to manage their own learning processes.MethodsThe study used in-depth interviews with students and employed thematic analysis to explore the experiences of self-regulated learning. Through this qualitative approach, key themes emerged, including motivation, the learning process, support systems, planning, and group dynamics.ResultsNoteworthy findings include the significance of clear guidelines regarding study hours and designated learning environments for students. Themes such as the learning process, planning, and group dynamics were highlighted as crucial factors in effective self-regulated learning. Additionally, motivation and the role of support systems were found to play essential roles in students’ learning outcomes.DiscussionThe findings suggest that even students who exhibit autonomous motivation benefit from additional tools and support mechanisms to enhance their self-study practices. Educators are encouraged to integrate activities that foster learning strategies and promote social relationships within student groups. The study emphasizes the importance of creating structured learning environments and support systems to facilitate effective self-regulated learning for all students.

DEVELOPMENT OF SCIENTIFIC COMPETENCE OF STUDENTSBY USING THE RESULTS OF RESEARCH ON HUMICSUBSTANCES IN THE EDUCATIONAL PROCESS

This paper examines the use of humic compounds in research activities as a waysof shaping students' research skills. A precondition for the analysis is to determine the research capabilities of undergraduate students, which will lead to the growth of an objective systematic phenomenon of learning. The research findings of this paper present objective knowledge as expressed in the conceptual framework of chemical education. To illustrate the meaning of scientific ability, we will investigate how undergraduate students in chemistry develop study abilities through diverse experiments. On the basis of the examination and abstraction, the relationship between undergraduate students' developments in scientific capability and their academic efforts is identified. In the procedure of higher learning, bachelor students' scientific engagement is organized, and study capabilities are developed by employing successful problem-oriented teaching approaches.One of the most understudied difficulties in practice is the use of technology for establishing a competence-based strategy for student training. The formation of competencies that make up the integral structure of personal and professional characteristics for the successful performance of educational functions. One of the key objectives is to develop the academic skills for prospective professionals in higher education institutes. The primary lines of learning have changed as society has evolved, and in accordance with this, the best specialist with a higher education is required to improve his knowledge.

Associative Learning and Active Inference.

Associative learning is a behavioral phenomenon in which individuals develop connections between stimuli or events based on their co-occurrence. Initially studied by Pavlov in his conditioning experiments, the fundamental principles of learning have been expanded on through the discovery of a wide range of learning phenomena. Computational models have been developed based on the concept of minimizing reward prediction errors. The Rescorla-Wagner model, in particular, is a well-known model that has greatly influenced the field of reinforcement learning. However, the simplicity of these models restricts their ability to fully explain the diverse range of behavioral phenomena associated with learning. In this study, we adopt the free energy principle, which suggests that living systems strive to minimize surprise or uncertainty under their internal models of the world. We consider the learning process as the minimization of free energy and investigate its relationship with the Rescorla-Wagner model, focusing on the informational aspects of learning, different types of surprise, and prediction errors based on beliefs and values. Furthermore, we explore how well-known behavioral phenomena such as blocking, overshadowing, and latent inhibition can be modeled within the active inference framework. We accomplish this by using the informational and novelty aspects of attention, which share similar ideas proposed by seemingly contradictory models such as Mackintosh and Pearce-Hall models. Thus, we demonstrate that the free energy principle, as a theoretical framework derived from first principles, can integrate the ideas and models of associative learning proposed based on empirical experiments and serve as a framework for a better understanding of the computational processes behind associative learning in the brain.

Export Persistence and Productivity in Vietnam: Who Learns?

The purpose of this study is to investigate the causal relationship between firms' export activities and their productivity, with a specific focus on identifying the source of productivity improvement by examining the persistence of export operations. Leveraging firm-level panel data from 2010 to 2015 in Vietnam, we employed a combination of Propensity Score Matching and Staggered Difference-in-Differences. Our findings indicate that the phenomenon of learning by exporting is evident across both consistent and intermittent exporters. For manufacturing enterprises, our analysis reveals no substantial variance in the learning by exporting effect between the steady and sporadic exporters. In contrast, within the service sector, we discern that intermittent exporters experience a more pronounced enhancement in labor productivity compared to their consistent exporting counterparts. Upon delving deeper into industry analysis, it becomes evident that the manufacturing and wholesale/retail trade sectors are the ones benefiting most from export activities. An interesting observation is that, within the manufacturing sector, we only find a positive impact on labor productivity with continuously exporting firms. This disparity implies that the mechanisms through which the learning-by-exporting effect operates may diverge between the manufacturing and service sectors. Furthermore, our empirical evidence reveals a direct positive correlation between export status and firm performance within privately owned enterprises. However, such a relationship was not evident for state-owned enterprises. To capitalize on the potential of export-driven growth, policymakers should adopt a nuanced approach, tailored to the unique dynamics of different industries and ownership structures. This underscores the importance of sector-specific support mechanisms, capacity-building initiatives for state-owned enterprises, and targeted export literacy programs for enterprises in fostering a conducive environment for sustainable economic growth in the Vietnamese context.

Review article: Back to life from being declared dead in the Resus Bay: An integrative review of the phenomenon of autoresuscitation and learning for ED.

This is a literature review of ED autoresuscitation. The impetus for this review was a case which revealed a lack of understanding about Lazarus syndrome among ED staff. The primary objective was to see the proportion of cases who survived neurologically intact to discharge and the time frame when this occurred after death had been declared. A secondary outcome was to see whether these studies mention whether bedside echo was performed prior to deciding whether to terminate resuscitation. A systematic search of five databases was undertaken with keywords, 'autoresuscitation', 'cardiac arrest' and 'emergency department'. Articles published in the English language were selected for inclusion. No time frame was selected because of the low number of articles. A total of 240 articles were identified, that yielded 26 cases that were relevant and could be synthesised to create a discussion on the current clinical guidelines around resuscitation. Our analysis demonstrates that of the 11 survivors who were discharged neurologically intact, the average age was 42.9 years; otherwise, the average was 62.6 years. The majority (23/26) 88% auto-resuscitated within 10 min after being pronounced dead. Only five patients are mentioned as having had a bedside echo prior to deciding to cease efforts. Under-reporting of autoresuscitation is suspected because of fears of blame. Passive monitoring for 10 min after resuscitation is ceased, is recommended. There is need for more data on this phenomenon to help inform further research on the topic.

Search for neurophysiological mechanisms of configurational learning

Configural learning is a form of associative learning in which the conditioned stimulus is a holistic set of stimulus elements rather than individual stimuli or their isolated properties. Successfully solving the task of such associative learning requires a holistic analysis of the entire configuration as a whole. The ability to analyze not only individual physical aspects of a stimulus or single objects in a visual scene, but also their holistic combinations, offers significant evolutionary advantages, as configurations often have substantially greater predictive power compared to individual stimulus elements or features. Moreover, the ability to holistically analyze combinations of stimulus field elements or features can be considered an initial, primitive manifestation of consciousness. In the present review, we consider the history of the development of the concept of configural learning, the main methodological avenues of investigation, and currently available neurophysiological data on the putative neural basis of this phenomenon. We find it most interesting to study the processes of configural learning in humans using modern neuroimaging methods, as they provide a glimpse into the holistic brain functioning. Finally, we consider the future tasks aimed to provide a more complete understanding of the neurophysiology of the configural learning phenomenon.

The visual statistical learning overcomes scene dissimilarity through an independent clustering process.

Contextual cueing is a phenomenon of visual statistical learning observed in visual search tasks. Previous research has found that the degree of deviation of items from its centroid, known as variability, determines the extent of generalization for that repeated scene. Introducing variability increases dissimilarity between multiple occurrences of the same repeated layout significantly. However, current theories do not explain the mechanisms that help to overcome this dissimilarity during contextual cue learning. We propose that the cognitive system initially abstracts specific scenes into scene layouts through an automatic clustering unrelated to specific repeated scenes, and subsequently uses these abstracted scene layouts for contextual cue learning. Experiment 1 indicates that introducing greater variability in search scenes leads to a hindering in the contextual cue learning. Experiment 2 further establishes that conducting extensive visual searches involving spatial variability in entirely novel scenes facilitates subsequent contextual cue learning involving corresponding scene variability, confirming that learning clustering knowledge precedes the contextual cue learning and is independent of specific repeated scenes. Overall, this study demonstrates the existence of multiple levels of learning in visual statistical learning, where item-level learning can serve as material for layout-level learning, and the generalization reflects the constraining role of item-level knowledge on layout-level knowledge.

Symposium 3: Evocative writing and lived experience descriptions for networked learning research

The present paper introduces evocative writing, advocated by autoethnographies, as an effective research method to capture the subtleties of real-life networked learning experiences, enabling researchers to observe and make sense of both the beautiful and the ugly of the phenomenon. Evocative writing practice can liberate researchers from the established academic tradition that unnecessarily devalues their subjectivity and limits their creativity by imposing the problematic normality of research objectivity. Writing is a central research act that needs to be successfully performed throughout the entire research project—not only to present project outcomes but also to formulate research problems, collect data, and validate outcomes. Despite its aesthetic and communicative merits, however, evocative researchers as human beings cannot fully grasp the structural essence of the lived experiences of networked learning phenomena beyond their own frame of reference. Here, the author believes that lived experience descriptions and related methodological techniques devised by phenomenologists can provide evocative networked learning researchers with a possible breakthrough. Based on the author’s own experiences, the author will demonstrate the effective use of evocative writing complemented by lived experience descriptions for networked learning research.

Where is the ‘WIL’ in Work-integrated Learning Research?

ABSTRACT Research often defines Work-integrated Learning (WIL) as an educational approach that provides students with work-based experiences. In this article, we argue that this approach definition of WIL is nonsensical and maintains a research terminology that fails to capture what WIL is, namely, a multidimensional learning phenomenon. Drawing on this argument, this article aims to explore and problematise how the term WIL is used in contemporary research. To achieve this aim, we draw on contemporary research and conduct a text analysis of 48 extended abstracts that were accepted for an international WIL conference in December 2022. The text analysis generated three recurring research phenomena that we relate to research. These are (i) WIL avoidance, when the WIL term is evaded although it could very well have been used, (ii) WIL washing, when the WIL term is used in a hollow manner, and (iii) WIL ambiguity, when the WIL term is used vaguely. We scrutinise how these research phenomena and the approach definition of WIL pose challenges to establishing a comprehensive research terminology that can bring about an increased understanding of what WIL is. Finally, we call for research to use a more careful and nuanced terminology that acknowledges WIL’s multidimensional nature.

Children’s Speech Errors Reflect Phonotactics That They Say and Hear

ABSTRACT Adults learn phonotactics from what they say and hear, and this learning is revealed in speech errors. Previous work on the transfer of phonotactic learning from perception to production found that adults learn the constraints in what they say instead of what they hear, unless they are monitoring what they hear for errors. We investigated whether children exhibit this same phonotactic learning phenomenon. Children alternated reciting tongue twisters containing experimental phonotactic constraints and listening to tongue twisters with the same or opposing phonotactic constraints. Participants performed either an error monitoring task or a phoneme identification task while listening. Children’s resulting speech errors reflected the constraints in what they said and, to some extent, in what they heard regardless of the task performed during the perception trials. This is a marked difference from experiments with adults and suggests that the transfer of phonotactic learning from perception to production may differ across the lifespan. We consider several developmental explanations for this difference including reading ability.

EDGE AI BASED PLANT DISEASE DETECTION SYSTEM

Agriculture is a crucial industry to humankind's continued existence. Simultaneously, digitalization's pervasive influence made it simpler to accomplish previously challenging jobs in a wide range of disciplines. The agriculture industry, for both the farmer and the consumer, would greatly benefit from technological and digital adaptation. Through the use of technology and consistent monitoring, illnesses can be detected early on and removed, resulting in a higher yield. The economic, social, and political lives of farmers and the entire agricultural industry are profoundly impacted by the health and productivity of their crops. Therefore, in order to detect the illnesses at the proper moment, it is essential to conduct careful monitoring at different phases of crop growth. However, humans may require more than their natural attire, and there may be situations when doing so would be deceiving. Accurate identification requires a system that can automatically recognise and categorise the numerous illnesses that can affect a given crop. The current proposed framework was inspired by this train of thought. The suggested framework is primarily concerned with the transfer learning phenomena based on VGG16, and the "Plant Village" dataset, which contains both damaged and healthy potato and tomato leaves, is being explored for implementation. Keywords: Transfer learning, VGG16, Plant Village.

Robustness of a macroscopic computer-vision wood identification model to digital perturbations of test images

Summary Distribution shift, a phenomenon in machine learning characterized by a change in input data distribution between training and testing, can reduce the predictive accuracy of deep learning models. As operator and hardware conditions at the time of training are not always consistent with those after deployment, computer vision wood identification (CVWID) models are potentially susceptible to the negative impacts of distribution shift in the field. To maximize the robustness of CVWID models, it is critical to evaluate the influence of distribution shifts on model performance. In this study, a previously published 24-class CVWID model for Peruvian timbers was evaluated on images of test specimens digitally perturbed to simulate four kinds of image variations an operator might encounter in the field including (1) red and blue color shifts to simulate sensor drift or the effects of disparate sensors; (2) resizing to simulate different magnifications that could result from using different or improperly calibrated hardware; (3) digital scratches to simulate artifacts of specimen preparation; and (4) a range of blurring effects to simulate out-of-focus images. The model was most robust to digital scratches, moderately robust to red shift and smaller areas of medium-to-severe blur, and was least robust to resizing, blue shift, and large areas of medium-to-severe blur. These findings emphasize the importance of formulating and consistently applying best practices to reduce the occurrence of distribution shift in practice and standardizing imaging hardware and protocols to ensure dataset compatibility across CVWID platforms.

You Can Make it Too Easy: Simulating Easy-To-Hard Effects in Auditory Perceptual Learning with an Unsupervised Neural Network Model of Plasticity

ABSTRACT The easy-to-hard effect is a phenomenon where training on initially easy perceptual discrimination contrasts before introducing hard contrasts yields greater perceptual learning than training with hard contrasts for the same amount of time. However, easy-to-hard effects can be erased if initial easy trials are made too easy. Here, we show that this seemingly paradoxical result naturally emerges out of an artificial neural network model of perceptual learning based on the incremental differentiation of stimulus representations: the self-organizing map (SOM). Like human listeners, networks show a sweet spot for easy-to-hard effects at intermediate levels of easy contrast somewhere between too easy and too hard. This trend is apparent across a wide range of free parameters. Analysis of network learning dynamics shows that easy-to-hard effects manifest when competition for network representational space is reduced (relative to constant hard training), but the learned stimuli are still similar enough to hard contrast stimuli to allow generalization. The data show that an incremental perceptual learning model can account for subtle characteristics of easy-to-hard effects where learning theories grounded in attentional discovery of relevant features cannot. We suggest several avenues for further development of the model in order to account for a wider range of auditory learning phenomena, its use in the optimization of auditory training regimens, and its role in elucidating perceptual learning mechanisms.

The impact of instructional units on accordance with Dienes model in motor behavior and learning some basic football skills for students.

The Denz model is one of the models of teaching based on cognitive theory within the theories that have interpreted the phenomenon of learning. The research also aimed to prepare educational units according to the Denz model. The researcher used the experimental curriculum to suit it. ) The experimental group and the Division (C) the control group and by (20) students for each group, and the study concluded that the Denz model has a positive impact on the superiority of the level of the experimental group students in motor behavior and learned some of the basic skills of football under research. The researcher recommended, based on the modern models of teaching, including the Denz model, which is the student's primary axis in order to achieve the best results.

Indigenous Wisdom-Based Literature at Buru Island: Situation and Need Analysis for Developing Indonesian Teaching Materials

The study of language and literature today are inseparable. Unfortunately, the phenomenon of Indonesian learning in junior high schools is in a hesitant position due to the lack of formulating literature as teaching material including indigenous wisdom-based literature that can threaten the extinction of indigenous literature. At Buru Island, literature learning is integrated into Indonesian subjects, but the teachers there are more focused on teaching language using general literature rather than indigenous wisdom literature. Therefore, this study aimed to explore the situation and needs analysis of the indigenous wisdom-based literature in teaching Indonesian language at Buru Island. To achieve the objectives of the study, the researchers employed Research and Development (R&D) applying Borg and Gall’s steps. This method has certain procedures for the information collecting data related to the situation and needs analysis of 350 junior high school students through questionnaire distribution, interview, and observation toward the process of Indonesian teaching in the classroom. The situation of learning literature in the study involved (1) the law of local content learning, (2) curriculum, (3) syllabus, (4) lesson plan, (5) coursebooks, (6) teachers’ competence, and (7) stakeholders’ concerns, while, the students’ need analysis involved (1) current ability and interest in literature, (2) feedback of students’ ability and interest in literature, (3) literature skills priority, (4) learning style, (5) literature learning facilities and infrastructure, (6) literature materials on indigenous wisdom, (7) coursebook of indigenous wisdom-based literature, and (8) learning approaches and strategies based on indigenous wisdom. The result shows that there were still many shortages in implementing of indigenous wisdom-based literature learning in junior high schools, so students’ ability and interest were lack. Therefore, the situation and need analysis becomes very important to be explored and to be a consideration in designing course books in indigenous wisdom-based literature for the future.

Development of an Integrated Project-Based Learning Module Based on Black Soybean Ethnoscience to Improve Students' Science Process Skills

Science process skills are one of the 21st-century skills that are important to optimize to train students to be skilled in solving problems. However, facts in the field show that science process skills are still relatively low because teachers do not yet understand how to develop science process skills, and there is a lack of teaching materials based on a scientific approach to developing science process skills. This research aims to develop an integrated Project-based Learning (PjBL) module for black soybean ethnoscience that is valid, practical, and effective for improving students' science process skills. The model for product development is ADDIE. The product's effectiveness was tested using a quasi-experiment with research subjects consisting of 91 students (46 experimental and 45 control group students). The results of the module developed meet valid and practical criteria. The results of product effectiveness tested using quasi-experiments show that the integrated PjBL module of black soybean ethnoscience effectively improves science process skills. They are increasing students' science process skills due to using contextual phenomena in learning.

Prevention of cross-language interference in the context of trilingual education (Russian, Kazakh, and English languages)

Relevance. The relevance of the study lies in the fact that in the modern world, trilingual education is becoming increasingly common, necessitating the exploration of methods, exercises, and approaches to reduce interference phenomena in language learning. Purpose. The purpose of the study is to identify factors contributing to cross-language interference in trilingual education and to develop strategies and methods for its prevention and minimisation. Methodology. To achieve the purpose, the following methods were used: hypothetical-deductive, questionnaire, correlation analysis, and comparative. Results. Results revealed key factors influencing cross-language interference across Russian, Kazakh, and English languages. They cover various language levels such as vocabulary, grammar, phonetics, as well as sociocultural aspects. The study highlights various methodological strategies and approaches that can be successfully applied to prevent cross-language interference, emphasising the active role of both learners and educators in the prevention process. Comparative analysis of English language instruction within trilingual education revealed that the majority of errors in oral and written language usage were linked to native language interference. It was also established that the degree of development of the relevant skills of students in both groups increased. However, in the first group, the growth rate reached an average of about 50%, while in the second group, the shift ranged from 25% to 38%. Conclusions. The study concludes that preventing cross-language interference in trilingual education (Russian, Kazakh, and English) requires targeted strategies and methods. Key factors influencing interference include vocabulary, grammar, phonetics, and sociocultural aspects. Effective prevention involves active participation from both learners and educators, with a focus on methodological strategies tailored to the specifics of trilingual education. Keywords: lexical skills; linguistic system; instructional materials; exercises; speech interaction

Analysis of Quantum Physics Lectures from the Perspective of the MBKM and OBE Based Higher Education Curriculum

Lecture analysis in the core courses of the study program contributes to the evaluation of the curriculum used. This field study was carried out to analyze Quantum Physics lectures from the perspective of a university curriculum based on Independent Learning Campus (MBKM) and Outcome-Based Education (OBE). Data collection techniques were carried out through observing the implementation of learning in the Quantum Physics course, interviews with lecturers teaching quantum physics courses, and reviewing curriculum tools in the form of curriculum books, semester lecture plans (RPS), and assessment documents. The instruments used refer to content standards, process standards and learning assessment standards listed in Permendikbud Number 3 of 2020, Permendikbudristek Number 56 of 2022, and Permendikbudristek Number 53 of 2023. The participants involved in this research were a lecturer and 29 students of the undergraduate physics education study program at one of the universities in Garut Regency. The lecturer in question is a lecturer who teaches quantum physics courses, while the students in question are final year students who are taking quantum physics courses in the odd semester of the 2023/2024 academic year. Data collection was carried out over the period October – November 2024. Data analysis was carried out qualitatively using a data triangulation approach. The results of data analysis show that in the Bachelor of Physics Education curriculum, the Quantum Physics course is in the group of upper-level compulsory courses with physics concept study material. From an MBKM perspective, this course can be converted to Program Pertukaran Mahasiswa (PMM) and Program Magang dan Studi Independen Bersertifikat (MSIB), but cannot be converted to the Teaching Campus Program. Conversion to the PMM program is carried out by taking courses in other study programs that have course learning outcomes that are related to quantum physics. Conversions to the MSIB program are carried out at companies or agencies related to the application of quantum physics concepts. From an OBE perspective, this course contributes to graduate learning outcomes in Specific Skills and supports the graduate's profile as a Physics Teacher. The special skill in question is being able to apply mathematical models in explaining physical phenomena in learning.

Variations in Student Approaches to Problem Solving in Undergraduate Biology Education.

Existing research has investigated student problem-solving strategies across science, technology, engineering, and mathematics; however, there is limited work in undergraduate biology education on how various aspects that influence learning combine to generate holistic approaches to problem solving. Through the lens of situated cognition, we consider problem solving as a learning phenomenon that involves the interactions between internal cognition of the learner and the external learning environment. Using phenomenography as a methodology, we investigated undergraduate student approaches to problem solving in biology through interviews. We identified five aspects of problem solving (including knowledge, strategy, intention, metacognition, and mindset) that define three qualitatively different approaches to problem solving; each approach is distinguishable by variations across the aspects. Variations in the knowledge and strategy aspects largely aligned with previous work on how the use or avoidance of biological knowledge informed both concept-based and nonconcept-based strategies. Variations in the other aspects revealed intentions spanning complete disengagement to deep interest with the course material, different degrees of metacognitive reflections, and a continuum of fixed to growth mindsets. We discuss implications for how these characterizations can improve instruction and efforts to support development of problem-solving skills.

The Hierarchical Discrete Pursuit Learning Automaton: A Novel Scheme With Fast Convergence and Epsilon-Optimality.

Since the early 1960s, the paradigm of learning automata (LA) has experienced abundant interest. Arguably, it has also served as the foundation for the phenomenon and field of reinforcement learning (RL). Over the decades, new concepts and fundamental principles have been introduced to increase the LA's speed and accuracy. These include using probability updating functions, discretizing the probability space, and using the "Pursuit" concept. Very recently, the concept of incorporating "structure" into the ordering of the LA's actions has improved both the speed and accuracy of the corresponding hierarchical machines, when the number of actions is large. This has led to the ϵ -optimal hierarchical continuous pursuit LA (HCPA). This article pioneers the inclusion of all the above-mentioned phenomena into a new single LA, leading to the novel hierarchical discretized pursuit LA (HDPA). Indeed, although the previously proposed HCPA is powerful, its speed has an impediment when any action probability is close to unity, because the updates of the components of the probability vector are correspondingly smaller when any action probability becomes closer to unity. We propose here, the novel HDPA, where we infuse the phenomenon of discretization into the action probability vector's updating functionality, and which is invoked recursively at every stage of the machine's hierarchical structure. This discretized functionality does not possess the same impediment, because discretization prohibits it. We demonstrate the HDPA's robustness and validity by formally proving the ϵ -optimality by utilizing the moderation property. We also invoke the submartingale characteristic at every level, to prove that the action probability of the optimal action converges to unity as time goes to infinity. Apart from the new machine being ϵ -optimal, the numerical results demonstrate that the number of iterations required for convergence is significantly reduced for the HDPA, when compared to the state-of-the-art HCPA scheme.