Learning Process Research Articles

Students’ understanding of vector operations: With and without physics education technology simulation

This study aims to investigate the influence of technology integration (physics education technology simulation) in physics learning. A quantitative method with a quasi-experimental post-test-only design was applied to reveal the differences in students’ abilities to operate vectors between the group that learned and tested using simulation and the group that learned using graphics only. The test consisted of 16 questions on the addition and subtraction of two vectors divided into one and two dimensions. Student response data were analyzed using descriptive statistics and Kruskal-Wallis test. The analysis results show that the vector operation score for experimental group 1, which learned vector operations through graphic learning using simulation and tested with the same simulation (86.15), is higher than experimental group 2, which learned vector operations through graphic learning using simulation (76.59), and the control group, which learned vector operations through graphic learning without simulation assistance (71.81). All three groups have higher average scores for one-dimensional than two-dimensional vector operations. They also have higher average scores for vector addition compared to vector subtraction operations. Kruskal-Wallis test results indicate a significant difference in the average vector operation scores for the three groups (ρ=0.021). This suggests that integrating technology in the learning and testing processes leads to a significant difference. Moreover, the difference is significant for one-dimensional vector operations (ρ=0.004) and not significant for two-dimensional vector operations (ρ=0.107). These findings could support the implementation of similar approaches at the university and high school levels, especially for vector-related topics, in both learning and testing processes.

Exploration of ChatGPT in basic education: Advantages, disadvantages, and its impact on school tasks

The introduction of ChatGPT into basic education is progressing rapidly, generating impacts that, in many cases, are unknown. Its impressive capability profiles it as a tool that will revolutionize teaching and learning processes, creating gaps that need to be understood and evaluated. The research aims to explore the advantages, disadvantages, and its impact on school tasks. It is an exploratory qualitative study; data were collected through semi-structured interviews with 110 participants from five schools in Tacna, Peru. The results reveal that ChatGPT provides information quickly and easily, with a variety of content and pedagogical strategies. Additionally, it serves for evaluation, knowledge consultation, and scheduling school tasks. Eight related disadvantages were identified: Easy access to information may encourage the habit of copying and pasting, fostering academic dependence that would affect the development of skills, such as inquiry, argumentation, analysis, and critical thinking. Also, students may misuse information, cheating on school tasks and affecting their quality and suitability, making them no longer useful for education, including synthesis, essays, monographs, organizers, summaries, and mathematical exercises.

ANALISIS KETERAMPILAN BERPIKIR KRITIS SISWA PADA PEMBELAJARAN BERBASIS MASALAH MATA PELAJARAN IPA DI SD

Critical thinking skills are the ability to solve problems and make decisions when facing a problem. Critical thinking skills can consist of the ability to analyze, interpret, evaluate, summarize, and synthesize various information to prevent negative impacts from occurring. The purpose of this study was to describe and identify students' critical thinking skills. The method used in this research is descriptive quantitative method. Data were collected through survey techniques in the form of questionnaires using test instruments. The results of this study are the average level of students' critical thinking skills at 54.75%. One of the efforts to improve students' critical thinking skills is to apply a problem-based learning model. This is in line with the purpose of science learning, which is to develop student’s' thinking skills in the learning process so that they can apply natural science concepts in their daily activities.

SURVEI KETERAMPILAN BERHITUNG PENJUMLAHAN DAN PENGURANGAN SISWA KELAS RENDAH DI SD PADA PEMBELAJARAN MATEMATIKA

This study aims to assess the numeracy skills of low-grade students in solving addition and subtraction problems, and present solution options to overcome the problems that arise. The approach used was quantitative method. The research subjects consisted of second semester low-grade students at State Elementary School 07 Petukangan Utara, Pesanggrahan District, South Jakarta City. The data collection techniques used were written tests and documentation. From the results of the study, it was concluded that overall, counting skills reached 74.85%, categorized as sufficient. Obstacles in learning arithmetic include misconceptions in operations involving zero numbers, not understanding addition and subtraction procedures, difficulty understanding story problems, and lack of accuracy in working on problems. Solutions proposed to overcome learning obstacles during the learning process include the application of math learning, providing constructive exercises and reinforcement of concepts that are not understood. Based on these conclusions, the suggestions given are that teachers should pay attention to the level of student understanding, teach concepts by emphasizing their definitions and properties, and conduct further research to reveal problems and find solutions.

Academic Integrity in Existing Classroom Resources and Teaching Learning Process for Children with Vision Impairment in Government Special Education Institutions of Punjab Pakistan

Purpose: The objective of this qualitative study was to evaluate the level of academic integrity in the provision and utilization of classroom resources and flow of the teaching-learning process for children with vision impairment (CWVI) at primary level. Design/Methodology/Approach: Non-participant classroom observations were conducted. Eight special education institutions working in various districts of Punjab were randomly selected. A self-developed, field experts validated classroom observation checklist was applied to conduct the classroom observations. All observations were carried out personally by the principal author. Researchers analyzed the data by descriptive statistics percentages of observed indicators for academic integrity. After that, a thematic analysis was carried out. Findings: The study showed that most observed classes had satisfactory classroom arrangement, teacher competence and classroom illumination. However, many observed classrooms were found with inadequate classroom arrangements and disturbing physical environment. There is a severe lack about effective use of need-based equipment, assistive aids, low-vision devices, lesson plans, student portfolios and any record of Students’ previous performance. Implications/Originality/Value: The study suggested that special education institutions should make all lacking facilities available. Refresher courses should be provided to teachers to improve their personality and teaching skills. The presence of Students’ portfolios and lesson plans should be assured.

Data Complexity: A New Perspective for Analyzing the Difficulty of Defect Prediction Tasks

Defect prediction is crucial for software quality assurance and has been extensively researched over recent decades. However, prior studies rarely focus on data complexity in defect prediction tasks, and even less on understanding the difficulties of these tasks from the perspective of data complexity. In this article, we conduct an empirical study to estimate the hardness of over 33,000 instances, employing a set of measures to characterize the inherent difficulty of instances and the characteristics of defect datasets. Our findings indicate that: (1) instance hardness in both classes displays a right-skewed distribution, with the defective class exhibiting a more scattered distribution; (2) class overlap is the primary factor influencing instance hardness and can be characterized through feature, structural, and instance-level overlap; (3) no universal preprocessing technique is applicable to all datasets, and it may not consistently reduce data complexity, fortunately, dataset complexity measures can help identify suitable techniques for specific datasets; (4) integrating data complexity information into the learning process can enhance an algorithm’s learning capacity. In summary, this empirical study highlights the crucial role of data complexity in defect prediction tasks, and provides a novel perspective for advancing research in defect prediction techniques.

"Ava en la noche", de Manuel Vicent: formación artística y concienciación política bajo la noche franquista

In "Ava en la noche" (2020), Manuel Vicent narrates the learning process of a young aspiring screenwriter and film director who, in the early sixties, shapes his conscience as he experiences Franco’s repression and perceives a demanding society of change. The objectives of this paper are to explore the novel from the theoretical perspective of the Künstlerroman (or “artist’s novel”), and to apply certain initiatory categories of the hero outlined by mythical studies. The analysis of these elements makes visible the vital and aesthetic phases that lead the protagonist to existential maturity, to his historicity and to the commitment of his filmic art in correlation with the questioning of the dictatorial regime.

Acute Stress Effects on Statistical Learning and Episodic Memory.

Stress is widely considered to negatively impact hippocampal function, thus impairing episodic memory. However, the hippocampus is not merely the seat of episodic memory. Rather, it also (via distinct circuitry) supports statistical learning. On the basis of rodent work suggesting that stress may impair the hippocampal pathway involved in episodic memory while sparing or enhancing the pathway involved in statistical learning, we developed a behavioral experiment to investigate the effects of acute stress on both episodic memory and statistical learning in humans. Participants were randomly assigned to one of three conditions: stress (socially evaluated cold pressor) immediately before learning, stress ∼15 min before learning, or no stress. In the learning task, participants viewed a series of trial-unique scenes (allowing for episodic encoding of each image) in which certain scene categories reliably followed one another (allowing for statistical learning of associations between paired categories). Memory was assessed 24 hr later to isolate stress effects on encoding/learning rather than retrieval. We found modest support for our hypothesis that acute stress can amplify statistical learning: Only participants stressed ∼15 min in advance exhibited reliable evidence of learning across multiple measures. Furthermore, stress-induced cortisol levels predicted statistical learning retention 24 hr later. In contrast, episodic memory did not differ by stress condition, although we did find preliminary evidence that acute stress promoted memory for statistically predictable information and attenuated competition between statistical and episodic encoding. Together, these findings provide initial insights into how stress may differentially modulate learning processes within the hippocampus.

Organizational learning in surgery in Tanzania's health system: a descriptive cross-sectional study.

Organizational learning is critical for delivering safe, high-quality surgical care, especially in low- and middle-income countries (LMICs) where perioperative outcomes remain poor. While current investments in LMICs prioritize physical infrastructure, equipment, and staffing, investments in organizational learning are equally important to support innovation, creativity, and continuous improvement of surgical quality. This study aims to assess the extent to which health facilities in Tanzania's Lake Zone perform as learning organizations from the perspectives of surgical providers. The insights gained from this study can motivate future quality improvement initiatives and investments to improve surgical outcomes. We conducted a cross-sectional analysis using data from an adapted survey to explore the key components of organizational learning, including a supportive learning environment, effective learning processes, and encouraging leadership. Our sample included surgical team members and leaders at 20 facilities (health centers, district hospitals, and regional hospitals). We calculated the average of the responses at individual facilities. Responses that were 5+ on a 7-point scale or 4+ on a 5-point scale were considered positive. We examined the variation in responses by facility characteristics using a one-way ANOVA or Student's t-test. We used univariate and multiple regression to assess relationships between facility characteristics and perceptions of organizational learning. Ninety-eight surgical providers and leaders participated in the survey. The mean facility positive response rate was 95.1% (SD 6.1%). Time for reflection was the least favorable domain with a score of 62.5% (SD 35.8%). There was variation by facility characteristics including differences in time for reflection when comparing by level of care (P = .02) and location (P = .01), and differences in trying new approaches (P = .008), capacity building (P = .008), and information transfer (P = .01) when comparing public versus faith-based facilities. In multivariable analysis, suburban centers had less time for reflection than urban facilities (adjusted difference = -0.48; 95% CI: -0.95, -0.01; P = .046). Surgical team members reported more positive responses compared to surgical team leaders. We found a high overall positive response rate in characterizing organizational learning in surgery in 20 health facilities in Tanzania's Lake Zone. Our findings identify areas for improvement and provide a baseline for assessing the effectiveness of change initiatives. Future research should focus on validating the adapted survey and exploring the impact of strong learning environments on surgical outcomes in LMICs. Organizational learning is crucial in surgery and further research, funding, and policy work should be dedicated to improving learning cultures in health facilities.

Evaluating the impact of cloud e-learning in higher education: An empirical investigation

The motivation for conducting this study is to investigate the potential of Cloud e-learning to address the high-cost and high-complexity challenges of conventional learning methods for the upgraded learning processes in higher education. The overall direction of this research is driven towards how the actual usage of Cloud e-learning module affects students’ perceptions and academic performance. A Cloud e-learning module is designed and developed to promote optimised resource utilisation in the e-learning processes in higher education. A pretest-posttest method was adopted to study the impact of Cloud e-learning usage among students and whether the diffusion of Cloud e-learning has caused a change in students’ perceptions. The pretest-posttest results and students’ academic performance were then analysed to examine the impact from the actual usage of Cloud e-learning module. The findings reveal that the change of students’ perceptions is time variant, indicating students’ mixed perceptions on the usage of Cloud e-learning module. Analysis evidently reveals that the use of Cloud e-learning improved students’ learning performance in theoretical subjects. This research is useful to educators and ICT practitioners in making informed decisions in adopting the right ICT infrastructures to support e-learning in higher education.

Longitudinal associations between language network characteristics in the infant brain and school-age reading abilities are mediated by early-developing phonological skills.

Reading acquisition is a prolonged learning process relying on language development starting in utero. Behavioral longitudinal studies reveal prospective associations between infant language abilities and preschool/kindergarten phonological development that relates to subsequent reading performance. While recent pediatric neuroimaging work has begun to characterize the neural network underlying language development in infants, how this neural network scaffolds long-term language and reading acquisition remains unknown. We addressed this question in a 7-year longitudinal study from infancy to school-age. Seventy-six infants completed resting-state fMRI scanning, and underwent standardized language assessments in kindergarten. Of this larger cohort, forty-one were further assessed on their emergent word reading abilities after receiving formal reading instructions. Hierarchical clustering analyses identified a modular infant language network in which functional connectivity (FC) of the inferior frontal module prospectively correlated with kindergarten-age phonological skills and emergent word reading abilities. These correlations were obtained when controlling for infant age at scan, nonverbal IQ and parental education. Furthermore, kindergarten-age phonological skills mediated the relationship between infant FC and school-age reading abilities, implying a critical mid-way milestone for long-term reading development from infancy. Overall, our findings illuminate the neurobiological mechanisms by which infant language capacities could scaffold long-term reading acquisition.

Experiences of medical students and faculty regarding the use of long case as a formative assessment method at a tertiary care teaching hospital in a low resource setting: a qualitative study

IntroductionThe long case is used to assess medical students’ proficiency in performing clinical tasks. As a formative assessment, the purpose is to offer feedback on performance, aiming to enhance and expedite clinical learning. The long case stands out as one of the primary formative assessment methods for clinical clerkship in low-resource settings but has received little attention in the literature.ObjectiveTo explore the experiences of medical students and faculty regarding the use of the Long Case Study as a formative assessment method at a tertiary care teaching hospital in a low-resource setting.MethodologyA qualitative study design was used. The study was conducted at Makerere University, a low-resource setting. The study participants were third- and fifth-year medical students as well as lecturers. Purposive sampling was utilized to recruit participants. Data collection comprised six Focus Group Discussions with students and five Key Informant Interviews with lecturers. The qualitative data were analyzed by inductive thematic analysis.ResultsThree themes emerged from the study: ward placement, case presentation, and case assessment and feedback. The findings revealed that students conduct their long cases at patients’ bedside within specific wards/units assigned for the entire clerkship. Effective supervision, feedback, and marks were highlighted as crucial practices that positively impact the learning process. However, challenges such as insufficient orientation to the long case, the super-specialization of the hospital wards, pressure to hunt for marks, and inadequate feedback practices were identified.ConclusionThe long case offers students exposure to real patients in a clinical setting. However, in tertiary care teaching hospitals, it’s crucial to ensure proper design and implementation of this practice to enable students’ exposure to a variety of cases. Adequate and effective supervision and feedback create valuable opportunities for each learner to present cases and receive corrections.

Beyond ‘Infodemic’: Complexity, Knowledge and Populism in COVID-19 Crisis Governance

ABSTRACT The concept of the ‘infodemic’ has become a popular explanation for the rejection of anti-COVID-19 crisis governance measures. In this paper, we argue that infodemic is an inherent property of society under free institutions misused to pursue an epistemically vicious political epistemology. Furthermore, we provide an alternative account of political epistemology of COVID-19 governance and popular resistance to it. Namely, we argue that 1) pandemics represent a complex problem, and some level of resistance to governance which restricts liberties while informed by ongoing scientific and political learning processes is inevitable, and 2) the resistance is exacerbated by the history of technocratization of governance and the exclusionary socio-economic inequalities which condition political and epistemic deficiencies easily exploitable by the political entrepreneurs of right-wing populism, particularly under the conditions of social media which gamifies public discourse. Thus, we argue, the correct response to the cultures of rejection of anti-COVID-19 measures is to change the underlying political and economic conditions and not to limit speech or restrict franchise as the infodemic diagnosis suggests.

An embodied perspective on an augmented reality game in school: pupil's bodily experience toward learning

There has long been an increased focus on and investment in digital technology in schools to improve the quality of education. While digital tools have gained access to pedagogical spheres, physical activity has been overlooked, as pupils often engage in activities that require minimal bodily movement. In this article, we discuss pupils’ experiences with learning through an augmented reality (AR)-based game application and explain how the application supports embodied learning. Digital tools, including gaming, can supplement traditional activities, motivate children to become physically active and enhance their learning experiences. Integrating technology and physical activity can create a more varied, meaningful, and dynamic school day, positively supporting pupils’ learning processes. The AR game associated with this study facilitated physical activity and learning experiences through a mobile device application. The empirical material for the study includes interviews with pupils participating in an AR game in mathematics. The findings show that participating in an AR game promoted embodied learning and positively impacted pupils’ motivation, engagement and learning processes. More specifically, AR facilitated learners’ engagement in the learning process by fostering their active involvement through physical and social collaboration and by enhancing the pupils’ joy of learning. Additionally, the pupils expressed that they enjoyed the application’s variations and the experiences that followed working collaboratively with the tasks. Moreover, they commonly found the physical and collaborative components of the AR game exciting and academically motivating. Studies on AR games and technology focusing on the opportunities and pedagogical foundations for their use in education are relevant in these precarious times. Indeed, more knowledge is needed on the ways creative and flexible learning processes that transpire within a technological learning environment influence embodied learning, knowledge that is essential for designing teaching and learning in the technical future.

Responsible learning organizations: a framework to embed responsible innovation within organizations

Purpose The purpose of this paper is to explore the extent to which the concept of learning organization can support the embedding of responsible innovation (RI) in organizations. Design/methodology/approach Based on literature in the fields of corporate social responsibility, learning organizations and quadruple helix collaborations, the authors constructed the responsible learning organization (RLO) framework for RI. With the framework, the authors want to show that the RLO can enable RI within organizations. Findings Based on this framework, the distinction is made between, on the one hand, the learning processes inside the organization, which resemble reflexivity, and, on the other hand, the learning processes that take place with stakeholders outside the organization, which resemble the other three core processes of RI: anticipation, inclusion and responsiveness. Based on these insights, the authors argue that if an organization wants to do good on innovation, which is seen as the core of RI, organization’s core values should guide that. Practical implications Organizational core values should be developed by means of learning inside the organization. Therefore, the process of reflexivity should be stressed more, and employees should be empowered to take part in developing these values, which in return can guide the organization as a compass through all the uncertainty it will encounter during the learning outside the organization when interacting with stakeholders. Originality/value The RLO framework for RI shows what learning processes organizations should facilitate first and what content should be at stake during these learning processes to embed RI. Furthermore, the framework puts emphasis on reflexivity as a condition for responsiveness, inclusion and anticipation.

Beyond experiential knowledge: a classification of patient knowledge

AbstractPatients’ experiential knowledge is increasingly documented as a valid form of knowledge in the health sector and is often said to be a source of valuable information to complement the knowledge of health professionals. Although this increased recognition is outlined in the health science literature and formalized in certain organizational and clinical contexts, it remains difficult for various actors of the health ecosystem to contour the different forms of knowledge patients acquire through their experience as well as to consider them as essential in co-building care plans and as an asset to build care relationships. The aim of this review is twofold: (1) to challenge the dominant model of knowledge in medicine and healthcare by making the various forms of patient knowledge more explicit and tangible and (2) to provide a better understanding of what experiential knowledge consists of by classifying the various forms of knowledge patient acquire, develop, and mobilize throughout their care journey. A narrative review allows to classify six types of patient knowledge according to their source of learning: embodied, monitoring, navigation, medical, relational, and cultural knowledge. The three main sources of learning, namely the self, the system, and the community grounds patients’ learning process in their health journey.

Error Correction and Adaptation in Conversational AI: A Review of Techniques and Applications in Chatbots

This study explores the progress of chatbot technology, focusing on the aspect of error correction to enhance these smart conversational tools. Chatbots, powered by artificial intelligence (AI), are increasingly prevalent across industries such as customer service, healthcare, e-commerce, and education. Despite their use and increasing complexity, chatbots are prone to errors like misunderstandings, inappropriate responses, and factual inaccuracies. These issues can have an impact on user satisfaction and trust. This research provides an overview of chatbots, conducts an analysis of errors they encounter, and examines different approaches to rectifying these errors. These approaches include using data-driven feedback loops, involving humans in the learning process, and adjusting through learning methods like reinforcement learning, supervised learning, unsupervised learning, semi-supervised learning, and meta-learning. Through real life examples and case studies in different fields, we explore how these strategies are implemented. Looking ahead, we explore the different challenges faced by AI-powered chatbots, including ethical considerations and biases during implementation. Furthermore, we explore the transformative potential of new technological advancements, such as explainable AI models, autonomous content generation algorithms (e.g., generative adversarial networks), and quantum computing to enhance chatbot training. Our research provides information for developers and researchers looking to improve chatbot capabilities, which can be applied in service and support industries to effectively address user requirements.

NON MAJORED STUDENTS’ PERCEPTIONS OF USING GRAMMARLY APPLICATION TO ASSIST THEIR ENGLISH WRITING PRACTICE

English writing proficiency is crucial for university students, for both academic pursuits and future professional communication. During the acquisition of English writing skills at university, a majority of students still make serious mistakes regarding grammar, spelling, and punctuation. Giving feedbacks on students' written work is regarded as important, for it not only helps improve students’ writing skills, but motivates their frequent practice as well. Nevertheless, that teachers face recurring issues such as unequal distribution of the courses whose contents focus more on other English skills; and huge class sizes somehow diminishes the quality of their feedback. As a result, students are encouraged to utilize feedback from Grammarly, an artificial intelligence technology to aid them in their writing practice. This paper investigated how students perceive feedback from Grammarly as a tool to correct mistakes in their written work and their perceptions toward using Grammarly in the learning process. The objective was to determine the features of Grammarly and students’ perception of using technology in learning to write. This study utilized a close-ended questionnaire with five indicators of Likert scale, with participants are 60 English non majored second - year students at Dong Nai Technology University. The findings suggested that the majority of students hold a positive opinion on the use of Grammarly to aid them in learning English writing.

Problem-solving skills of Sulu State College freshmen students in flexible learning education: An assessment

The pandemic has prompted the adoption of online, modular, and blended learning modalities, emphasizing the importance of integrating these in daily teaching and learning processes. Problem-solving skills, considered crucial for 21st-century decision-making, are also essential. This study aimed to analyze the level of problem-solving skills of the freshmen college students in Sulu State College in (i) modular learning, (ii) online learning, and (iii) blended learning. Purposive sampling was used to sample A questionnaire adapted from related studies was used to elicit quantitative data using a 5-point modified Likert Scale. The freshmen college students were randomly sampled (n=119) from six schools in the college. Findings indicated that freshmen college students at Sulu State College demonstrated high competence in problem-solving across three learning modalities. Each modality offered unique benefits that effectively enhanced the students' mathematical problem-solving abilities. In modular learning, students felt confident in managing math problems independently highlighting the empowerment and self-learning capacity inherent in this approach. Online learning also proved effective, with students showing high competence in problem-solving because of flexibility and accessibility. Blended learning was particularly beneficial, with students reporting the highest levels of competence because it enhanced engagement, creativity, and problem-solving skills by providing a comprehensive and flexible learning experience.

Study on Intelligent Scoring of English Composition Based on Machine Learning from the Perspective of Natural Language Processing

Knowledge management is crucial to the teaching and learning process in the current era of digitalization. The idea of "learning via working together" is making Natural Language Processing a popular tool to improve the learning process based on the intelligent system for evaluating the composition. English language learning is highly dependent on the composition written by the students under various topics. Teachers are facing huge difficulties in the evaluation of the composition as the level of writing by the students will vary for individual. In this research, Natural Language Processing concept is utilized for getting trained with the student's writing skills and Multiprocessor Learning Algorithm (MLA) combined with Convolutional Neural Network (CNN) (MLA-CNN) for evaluating the composition and declaring the scores for the students. The model's composition scoring rate is validated using a range of learning rate settings. Some theoretical notions for smart teaching are proposed, and it is hoped that this automatic composition scoring model would be used to grade student writing in English classes. When applied to the automatic scoring of students' English composition in schools, the suggested composition scoring system trained by the MLP-CNN has great performance and lays the groundwork for the educational applications of ML inside AI. The study results proved that the proposed model has provided an accuracy of 98%.