Influence Learning Performance Research Articles

Effects of adaptive scaffolding on performance, cognitive load and engagement in game-based learning: a randomized controlled trial

BackgroundWhile game-based learning has demonstrated positive outcomes for some learners, its efficacy remains variable. Adaptive scaffolding may improve performance and self-regulation during training by optimizing cognitive load. Informed by cognitive load theory, this study investigates whether adaptive scaffolding based on interaction trace data influences learning performance, self-regulation, cognitive load, test performance, and engagement in a medical emergency game.MethodsSixty-two medical students from three Dutch universities played six game scenarios. They received either adaptive or nonadaptive scaffolding in a randomized double-blinded matched pairs yoked control design. During gameplay, we measured learning performance (accuracy, speed, systematicity), self-regulation (self-monitoring, help-seeking), and cognitive load. Test performance was assessed in a live scenario assessment at 2- and 6–12-week intervals. Engagement was measured after completing all game scenarios.ResultsSurprisingly, the results unveiled no discernible differences between the groups experiencing adaptive and nonadaptive scaffolding. This finding is attributed to the unexpected alignment between the nonadaptive scaffolding and the needs of the participants in 64.9% of the scenarios, resulting in coincidentally tailored scaffolding. Exploratory analyses suggest that, compared to nontailored scaffolding, tailored scaffolding improved speed, reduced self-regulation, and lowered cognitive load. No differences in test performance or engagement were found.DiscussionOur results suggest adaptive scaffolding may enhance learning by optimizing cognitive load. These findings underscore the potential of adaptive scaffolding within GBL environments, cultivating a more tailored and effective learning experience. To leverage this potential effectively, researchers, educators, and developers are recommended to collaborate from the outset of designing adaptive GBL or computer-based simulation experiences. This collaborative approach facilitates the establishment of reliable performance indicators and enables the design of suitable, preferably real-time, scaffolding interventions. Future research should confirm the effects of adaptive scaffolding on self-regulation and learning, taking care to avoid unintended tailored scaffolding in the research design.Trial registrationThis study was preregistered with the Center for Open Science prior to data collection. The registry may be found at https://osf.io/7ztws/.

Exploring the factors influencing academic learning performance using online learning systems

-Online learning has become vital and fundamental for learning success in higher education institutions to cope with various learning methodologies or crises such as COVID-19. Therefore, this study investigates factors influencing the academic learning performance among diploma and bachelor's degree students who utilize online e-learning systems in Jordan. Using a conceptual model developed from an extensive previous literature review, the study used a quantitative research methodology to collect data via survey questionnaires. Using PLS-SEM, the empirical analysis of 846 questionnaires collected from Jordanian students demonstrates that task-technology fit and students' satisfaction positively influence learning performance and contribute significantly to student academic success using online learning systems. While the quality of system, service, and information are critical determinants of task-technology fit, student interaction, and instructor interaction are critical determinants of student satisfaction. The study highlights the importance of user-friendly interfaces, effective communication channels, collaboration, and positive learning environments. The findings provide practical insights for universities, online learning system designers, administrators, and instructors to enhance student-learning outcomes. Additionally, system providers can use these findings to address essential successful tools and features needed to create effective and efficient online learning environments. This study highlights practical implications that support higher education institutions' efforts to enhance their online e-learning systems quality and improve student-learning outcomes while helping system providers address essential successful tools and features needed.

Examining Blended Learning Adoption Towards Improving Learning Performance in Institutions of Higher Education

Institutions of higher education are implementing Blended Learning (BL) approaches to supplement traditional courses in enhancing students’ learning experiences. However, only fewer studies have examined BL acceptance based on the determinants that influence students’ perception towards BL integration in improving learning performance. Accordingly, this study employs the theory of Technology Acceptance Model (TAM) and Information System (IS) success model to develop a model to examine the determinants that influence students’ perception towards BL integration and acceptance as a mode of study to improve learning performance. Survey questionnaire was designed, and data was gathered from 1169 students to empirically validate the designed model. Accordingly, Partial Least Square-Structural Equation Modeling (PLS-SEM) was applied to analyze the survey data. The results suggest that system quality, information quality, and service quality significantly impact students’ acceptance of BL. Moreover, results reveal that perceived usefulness of BL, perceived ease of use of BL, attitude towards using BL, intention to use BL, and actual use of BL were proven to be key determinants that should be considered in improving students’ acceptance of BL. Additionally, results indicate that students’ acceptance of BL significantly influences learning performance. Implications from this study provide insights on how institutions can improve students’ integration of BL initiatives in both physical and digital learning environments.

Input Modality and its Effect on Memory Recall

One’s learning performance may be influenced by many internal and external factors. In addition to one’s cognitive ability, matters related to the academic context such as learning materials, contents and instruction can regulate and influence learning performance. The study aimed to examine the effects of different input modalities on learning performance by measuring memory recall success. A total of 96 participants took part in an experimental study employing a between-subject design. They were randomly assigned to one of the three groups that were presented with either visual or auditory or a combination of visual-auditory inputs. In the study phase, the visual input group was asked to read the inputs which were visually presented to them. As for the auditory group, the participants were required to listen to the inputs presented auditorily to them. The visual-auditory group did both simultaneously (seeing and listening to the inputs) as the inputs combined both visual and auditory presentation. In the test phase, they were required to recall words that they could best recall from the study phase. Analysis of ANOVA revealed a statistically significant difference between the different input modalities on the participant’s ability to recall words. It signifies that learning materials that are presented both in audio and visual are better recalled compared to materials learned in a single modality (either visual or audio alone). The modality effect uncovered in the present study has important instructional implications related to the presentation of learning materials to optimise learners’ ability to learn.

Influence of Learning Intervention on Online Learners’ Performance

With the expansion of the online learning scale and the rapid development of learning analysis techniques, learning systems can completely record learners’ online learning behavior. What types of learning intervention measures can influence learning performance? How is the intervention working? The above questions are the focus of online courses and emphasize improving the online learning effect. In this research, 96 undergraduates (Classes 1 and 2, Grade 2) majoring in civil engineering and enrolled in the Engineering Surveying online course at the College of Transportation Engineering, Huanghe Jiaotong University, Henan Province, were selected as the research objects and randomly divided into two groups (the experimental group (N = 48) and the control group (N = 48)). Then, conducted a 15-week sustained intervention study through quasi-experimental research, and verified the effectiveness of different types of intervention measures on the learners’ learning performance. Next, a one-way analysis of variance was conducted, based on the pretesting of the performance data, the quality of online discussion posts, the effective learning duration, and the online final test results. Research results showed no obvious differences between the experimental group and control group in the online final test results from the previous semester (P = 0.347). The online learners’ learning performance was influenced by three aspects of the learning intervention, that is, apparent differences in the posting quality in the learning prompt intervention (T = 8.23, P < 0.01), the online learning duration in the process monitoring intervention (T = 23.19, P < 0.01), and the online final test results in the achievement incentive intervention (T = 6.08, P < 0.01). The research results have an important reference value for implementing intervention strategies in the online learning environment, judging the effectiveness of such strategies according to curve changes in performance, and using the mass data of learners recorded by online learning platforms.

The effects of cognitive- and affective-based trust on students’ knowledge sharing and learning performance during the Covid-19 pandemic

This study examined the effects of cognitive and affective-based trust on knowledge sharing among students, which influences learning performance during the COVID-19 pandemic. A survey was conducted with 730 participants, and analysis was carried out using structural equation modeling (SEM) based on the uses and gratifications (U&G) theory. The results showed that cognitive and affective trust significantly affects students’ knowledge sharing behavior on Facebook, which further influences learning performance. This study also showed that social media had become a tool for social interaction and learning, which is crucial to students during the COVID-19 pandemic.

Demotivating Factors of English Learning for Chinese Middle-school Learners

Demotivation has not been extensively researched in the second language study compared with a well-investigated field on learning motivation. Motivation is significant to influence learning performance of language that students will gain. According to the reviews on many previous research solving demotivated English learners issues, the study specifically pays attention to Chinese younger middle school ESL (English as a second language) learners, as analysis of learners learning experiences in public education might promote findings on influencing factors of demotivation. In this research, it focuses on the demotivated English learners, and explores the main factors for deficiency of motivation. The instrument applied in this study is a questionnaire modified from Sakai and Kikuchis [20] and focusing on 6 possible demotivating factors from literature review, which includes 28 items and has been tested on 197 Chinese ESL younger students. The results in this paper illustrate that students might be positively influenced by teachers. However, features of classes and students English learning experiences are considered as the most demotivation items by Chinese younger learners of English study.

The Influence of Online Learning Behavior on Learning Performance

Online education is a significant part of information education. It is an effective way to uncover online learning mechanisms and improve the quality of online teaching by exploiting the behavioral data of online learning platforms for learning performance prediction and analysis. In this paper, we focus on the learner’s learning behavior in an online teaching scenario and explore the predictive effectiveness and impact mechanism of each behavioral feature by building a predictive model based on a machine learning algorithm. Experimental results show that three behavioral characteristics, namely the number of visits to course materials, lecture review time, and assignment, intensively influence learning performance. By comparing various machine learning algorithms, it is found that the random forest algorithm has better prediction results.

Media Education through Digital Games: A Review on Design and Factors Influencing Learning Performance

In the past two decades, a considerable amount of research has focused on digital games as part of media education. Digital game-based learning (DGBL) is identified as a potential pedagogical approach to enhance learning in the digital era. In light of the increased number of academic articles on educational games, this study considers the development and the factors that influence learning performance among children by providing a thematic review of the literature available on DGBL. Findings show that despite following developmental standard procedures, a distinct perspective between the game designer and the educator is essential. Three major approaches have been identified, namely the learner-centered, the game-centered and the model approaches. Learning processes that use digital games show empirically positive results as well as the great influence in terms of intrinsic motivation, game features and overall learning experience.

New evidence on technological acceptance model in preschool education: Linking project-based learning (PBL), mental health, and semi-immersive virtual reality with learning performance.

Despite significant research on student learning performance, the literature on preschool education is limited. The learning performance of different institutes in China has not been satisfactory, and students are not given enough technological resources to help them improve their learning performance. Although Chinese preschool students are active learners, their learning performance is inadequate. As a result, this research aimed to discover how project-based learning, semi-immersive virtual reality, and mental health influence learning performance. For data collection, 800 questionnaires were distributed to high schools, and 290 valid questionnaires were considered for the data analysis using Smart PLS-SEM. According to the study's findings, project-based learning is critical for improving learning performance. This study's findings are significant because they show that mental health and semi-immersive virtual reality significantly mediate the relationship between project-based learning and learning performance. The study's findings are critical for educational institutions interested in improving student performance through project-based learning opportunities. Furthermore, because it employs an innovative technology acceptance model, this study has significant practical implications for project-based learning and student learning performance.

The Effect of Using Artificial Intelligence on Learning Performance in Iraq: The Dual Factor Theory Perspective

The adoption of artificial intelligence applications in higher education plays an important role in the improvement of the quality of education and learning practices and overcomes many educational' issues. The purpose of this study is to examine the factors influencing learning performance by using artificial intelligence in the educational process. The research model has been developed based on dual factor concept through examining “enablers” and “inhibitors” factors of artificial intelligence adoption in higher education toward improving the Learning Performance. The research model has been built based on a combination of the following theories, constructivism, TAM3, UTAUT, BM, status quo bias theory. The hypothesized model is validated empirically via a questionnaire including 57-item based on 5-point Likert scales completed by 383 respondents (random sampled). Structural equation modeling was used to evaluate the proposed model by analyzing the confirmatory factor and path effects across the AMOS software. The results demonstrate that the indicators of model fitness showed good fit. As for the results of the hypothesis test, it is clear that the results of the analysis show that the interaction and the engagement of learning have a significant effect on the collaboration for learning and thus have a significant effect on the learning performance. Perceived enjoyment, perceived usefulness, and perceived ease of use have a significant effect on using artificial intelligence. Facilitating conditions have no significant impact on using artificial intelligence. Consciousness has a positive effect on use while perceived risks and resistance do not significantly affect use and learning performance. The use of artificial intelligence has a positive and significant effect on learning performance.

How Smart Technology Affects the Well-Being and Supportive Learning Performance of Logistics Employees?

The rapid improvement of technologies such as artificial intelligence in recent years has resulted in the development of smart technologies (ST) that can influence learning performance in different fields. The purpose of study is to explore the link between smart technology and learning performance. Using the S-O-R model as a framework, the researchers argue that smart technology (Stimuli) will increase corporate trust, self-efficacy, and well-being (Organism), resulting in improved learning performance (Response). The current model regards corporate trust and self-efficacy as relationship factors and investigates their direct influence on employee well-being and learning performance and the mediating role played by these variables. Additionally, the function of employee well-being in moderating the relationship between corporate trust, self-efficacy, and employee learning performance is also explored. The respondents (n = 516) in the present study are made up of employees from 10 logistics companies located in China. The data analysis is conducted using the AMOS software. The results show that that smart technologies can affect learning performance through corporate trust, self-efficacy, and employee well-being. The implementation of smart technology initiatives by corporations may provide positive workplace outcomes for employees (increased well-being), corporations (more engagement in workplace learning performance), and the relationship between employees and the companies that employ them (corporate trust and self-efficacy).

Blockchain Technology Enhances Sustainable Higher Education

This research investigates blockchain technology, focusing on the influence of motivation on collaborative work, which positively influences learning performance in Higher Education Institutions (HEI). In addition, blockchain technology is correlated with decentralisation, security and integrity, and anonymity and encryption. It can also be perceived as a consensus mechanism, rewarding students, professors, and universities as a smart contract. Therefore, this technology has been used to improve higher education. It also allows less informed people to interact with better-informed peers and mentors. Finally, this study aims to enhance the current state of blockchain applications comprehension. The methodology used for this research includes document analysis, literature review, content analysis (blockchain platforms), the case study method, and the survey method. In statistical considerations, aiming to evaluate indicators, this research presents the Composite Reliability Analysis, Cronbach Alpha Coefficients, and the Bootstrapping method (Variance Inflation Factor). All these analyses aimed to present a designed research model. This exploratory research gathered data from 150 students at 3 universities in Serbia, Romania, and Portugal. As demonstrated, using student motivation has a significant and positive impact on the quality of student collaborative work. Student collaborative work also correlates with students’ higher level of engagement in the educational process, and the more engaged students are, the better their learning outcomes will be. As a result, in higher education, student involvement boosted learning outcomes. Researchers found that motivation, teamwork, and student involvement were important factors in improving student learning outcomes, as were blockchain-based tools. The results from the quantitative analysis indicate that Collaborative work, Motivation, Engagement, MOOCs, AR, VR, Gamification, and Online class were associated with learning performance.

Leisure Satisfaction Influences Learning Performance Among Community College Students

Many adults choose community college courses for continued learning to enrich themselves and satisfy their leisure needs, despite having completed formal education. We explored the relationship between learning motivation, learning satisfaction, leisure satisfaction, and learning performance among community college students attending classes in Taipei City. A total of 1,011 participants were recruited. Structural equation modeling was used to examine the validity of the questionnaires and test our hypotheses. Furthermore, we determined whether the two types of satisfaction acted as mediators by testing a dual mediation paths model. Learning motivation, learning satisfaction, leisure satisfaction, and learning performance were significantly and positively correlated. Additionally, learning and leisure satisfaction had complete mediating effects, with the indirect effect of learning satisfaction being relatively stronger than that of leisure satisfaction.

IMPACT OF SOCIAL MEDIA USAGE AND ACTIVE COLLABORATIVE LEARNING ON STUDENT ENGAGEMENT, SATISFACTION, AND LEARNING PERFORMANCE: GHANA AS GEOGRAPHIC AREA OF STUDY

This research aims to explore how social media use improves higher level education in Ghana. Emphatically, it attempts to investigate the effect of social media use and active collaborative learning on student engagement, satisfaction and learning performance. A close-ended questionnaire was administered through online survey to collect data from 429 higher education students. The relationship between variables were tested using partial least square structural equation modeling (PLS-SEM). The research findings involve the significant effect of social media usage and active collaborative learning on student engagement, satisfaction, and learning performance. As per result development, student engagement positively affected satisfaction, which in turn influences learning performance. Moreover, this study concludes that effective use of social media, active collaborative and student engagement via social media enhances learning and satisfaction. The present study also offers several theoretical and practical implications for educational institutions and research directions for upcoming scholars. KEYWORDS: Social media use, active collaborative learning, student engagement, student satisfaction, student learning performance.

Peroxiredoxin 6 Knockout Mice Demonstrate Anxiety Behavior and Attenuated Contextual Fear Memory after Receiving Acute Immobilization Stress.

Stress can elicit glucocorticoid release to promote coping mechanisms and influence learning and memory performance. Individual memory performance varies in response to stress, and the underlying mechanism is not clear yet. Peroxiredoxin 6 (PRDX6) is a multifunctional enzyme participating in both physiological and pathological conditions. Several studies have demonstrated the correlation between PRDX6 expression level and stress-related disorders. Our recent finding indicates that lack of the Prdx6 gene leads to enhanced fear memory. However, it is unknown whether PRDX6 is involved in changes in anxiety response and memory performance upon stress. The present study reveals that hippocampal PRDX6 level is downregulated 30 min after acute immobilization stress (AIS) and trace fear conditioning (TFC). In human retinal pigment epithelium (ARPE-19) cells, the PRDX6 expression level decreases after being treated with stress hormone corticosterone. Lack of PRDX6 caused elevated basal H2O2 levels in the hippocampus, basolateral amygdala, and medial prefrontal cortex, brain regions involved in anxiety response and fear memory formation. Additionally, this H2O2 level was still high in the medial prefrontal cortex of the knockout mice under AIS. Anxiety behavior of Prdx6−/− mice was enhanced after immobilization for 30 min. After exposure to AIS before a contextual test, Prdx6−/− mice displayed a contextual fear memory deficit. Our results showed that the memory performance of Prdx6−/− mice was impaired when responding to AIS, accompanied by dysregulated H2O2 levels. The present study helps better understand the function of PRDX6 in memory performance after acute stress.

Organisational learning, learning organisation, and learning orientation: An integrative review and framework

Organisational Learning (OL) is essential for the survival of an organisation and has led to a significant amount of conceptual and empirical studies. However, no attempt has yet been made to track the overall evolution of OL literature along with the inter-related concepts of learning organisation and organisational learning orientation. Therefore, the present study attempts to fill this gap and track the interdisciplinary flow of knowledge by applying a structural methodology called Systematic Literature Network Analysis (SLNA). The results reveal four main areas of investigation within the field: i) the fundamentals of OL; ii) OL in relation to managerial and economic variables; iii) management of learning organisation; iv) learning orientation in relation to managerial and economic variables. Furthermore, this review contributes by arranging the findings into a theoretical framework which is termed organisational learning chain. Based on the co-analysis of main themes and key concepts detected, the framework integrates and highlights the factors that influence learning performance in and by organisations. Finally, several further research avenues are discussed, and the benefits of the applied review methodology are highlighted.

Factors affecting students’ learning performance through collaborative learning and engagement

ABSTRACT In higher educational institutes, developing classrooms for active learning is becoming a part of comprehensive educational drive for students involving and engaging in learning. For this purpose, influence of social factors on collaborative learning and engagement has been investigated which will influence learning performance of students. The study looked at following areas: (a) the ability of social factors for developing collaborative learning and engagement and (b) whether collaborative learning and engagement mediate a link between social factors and student’s learning performance. Constructivism theory has been utilized to observe the student’s learning behavior. Data have been collected through questionnaires from university students. Findings evaluated through structural equation modeling (SEM), shows that social factors, i.e. interaction with peers and teachers, social presence, and usage of social media positively impact active collaborative learning and student involvement, thus affecting their learning performance. The findings also provide evidence for double mediation used in this study. As online learning is becoming more prevalent in education, it has been concluded that overall collaborative learning and engagement with influence of social factors improve activities of students learning; therefore, their usage should be stimulated in teaching and learning in higher educational institutions as it influences students’ academic development.

The Neonicotinoid Insecticide Imidacloprid Disrupts Bumblebee Foraging Rhythms and Sleep.

SummaryNeonicotinoids have been implicated in the large declines observed in insects such as bumblebees, an important group of pollinators. Neonicotinoids are agonists of nicotinic acetylcholine receptors that are found throughout the insect central nervous system and are the main mediators of synaptic neurotransmission. These receptors are important for the function of the insect central clock and circadian rhythms. The clock allows pollinators to coincide their activity with the availability of floral resources and favorable flight temperatures, as well as impact learning, navigation, and communication. Here we show that exposure to the field-relevant concentration of 10 μg/L imidacloprid caused a reduction in bumblebee foraging activity, locomotion, and foraging rhythmicity. Foragers showed an increase in daytime sleep and an increase in the proportion of activity occurring at night. This could reduce foraging and pollination opportunities, reducing the ability of the colony to grow and reproduce, endangering bee populations and crop yields.

What’s load got to do with it? A cognitive-ergonomic training model of simultaneous interpreting

ABSTRACT The study of ergonomics has the potential to improve human performance not only in occupational sectors, but also in educational settings, where they can influence learning performance. It has long been acknowledged that instructional design can have direct effects on learning outcomes, provided it considers the underlying cognitive architecture of the learner. Relevant design features include the sequencing of tasks and the provision of cues using different types of media. The cognitive ergonomics (CE) of a learning environment, therefore, address the interaction among the key features of instructional design, the learning content, and the learner. Starting from the premise that simultaneous interpreting (SI) is a complex cognitive activity likely to generate high levels of intrinsic load in traditional apprenticeship-based training models, the primary research focus of this paper is to describe a training model built on CE-based multimodal activities. These activities are described in terms of their CE design that aims at making available the necessary cognitive resources for germane processing and promoting the acquisition of schemas through practice.