General Learning Theory Research Articles

How much active teaching should be incorporated into college course lectures to promote active learning?

A long-standing controversy in the learning sciences involves the appropriate balance between more didactic forms of instruction (e.g., lecture) and those that involve more active teaching (e.g., student learning activities). There have been calls for second generation research that examines how much class time should be allocated to student learning activities and how much to lecture to maximize student learning in college courses—a question of the appropriate mix of instructor lecture and student activity. The purpose of the present study was to systematically compare the effects on learning outcomes of two mixtures of learning activities and lecture during a college course on research methods: mostly lecture (consisting of ∼67 % to 75 % lecture and ∼25 % to 33 % learning activities), and mostly activity (consisting of ∼67 % to 75 % learning activities and ∼25 % to 33 % lecture). In a between-subjects design, students in a research-methods in psychology course experienced in-class lessons that were mostly lecture or mostly activity across two different lessons. Participants in the mostly activity condition scored significantly higher on an assessment of learning than those in the mostly lecture condition for a lesson on single-case research designs (d = 0.38) which was less complex but performance between the two instructional conditions was similar for the lesson on direct observational methods which was more complex. Theoretical implications involve potential refinements to generative learning theory. Practical implications involve recommendations for when to provide high amounts of student learning activities during a class period.

Generative learning activities for online multimedia learning: when summarizing is effective but drawing is not.

The goal of this study is to determine whether two commonly used generative learning activities for text-based lessons-writing a summary or creating a drawing-help students learn from a multimedia lesson involving animations with short text captions without prior training in the generative activities. Students viewed a series of four annotated animations on greenhouse gases. During pauses between the animations, students were asked to generate a written summary, to create a drawing, or to do both, whereas a control group viewed the lesson without any generative learning activities. Students were tested immediately (Experiment 1) or after a one-week delay (Experiment 2). In both experiments, students who produced written summaries scored significantly higher on the posttest than those who engaged in no generative learning activities (d = 0.48 in Experiment 1, d = 0.54 in Experiment 2), but there was no significant difference on the posttest for students who generated drawings compared to those who engaged in no generative learning activities. In addition, those who engaged in drawing and summarizing did not have significantly different posttest performance than those engaged in summarizing alone. We conclude that writing summaries during a highly visual animated lesson is effective for learning, possibly because it encourages students to engage in generative processing during learning more than drawing and we discuss potential reasons for this in the discussion. This work helps extend generative learning theory by pinpointing potential boundary conditions for learning by drawing and learning by summarizing.

Psychological responses to political hostility: a study on aggression, bullying, and well-being in Qatar

ABSTRACT In 2017, the Gulf crisis led to a blockade that severely restricted Qatar’s air, land, and sea access. This political crisis had far-reaching consequences, particularly affecting cross-national families and children. This qualitative analysis explores the effects of the blockade’s political instability on individuals and families, specifically for Qatari citizens married to non-Qatari spouses and their cross-national children. Applying the General Aggression Model and Social Learning Theory, we interviewed 24 individuals residing in Qatar from nations directly affected by the crisis (Bahrain, Egypt, Saudi Arabia, and the United Arab Emirates). Two main themes emerged: first, the characteristics of aggressive and bullying behaviour, and second, the impacts on the well-being of cross-national families. The results showed that Qatari women and their children suffered disproportionately due to gender-based citizenship rights issues. The impacts on their well-being included heightened anxiety, depression, feelings of danger, uncertainty, and division within individuals, families, and communities. Recommendations include increasing collaborative efforts between governments, educational institutions, and community-based organizations, which are crucial to addressing aggressive and bullying behaviour across all age groups fostering a more harmonious and resilient society.

Entrepreneurship Learning with Islamic Identity (Case Study at Universitas Nahdlatul Ulama Surabaya)

Various efforts have been made to develop innovative entrepreneurship learning models. Universitas Nahdlatul Ulama Surabaya (Unusa) claims to have implemented Islamic self-identity entrepreneurship learning. This research aims to uncover the essence of Islamic self-identity entrepreneurship learning and its process. The study utilizes entrepreneurship learning theory and Islamic economic principles to analyze the findings, supported by general learning theory and Islamic entrepreneurship concepts. The research finds that the concept of Islamic self-identity entrepreneurship learning at Unusa fundamentally serves as coursework oriented towards Ilahiyah economics and Islamic economic principles (tauhid, khalifah, and ‘adl). The Islamic self-identity entrepreneurship learning process at Unusa is carried out through five phases: planning, theory delivery, learning practice, business implementation, and ongoing evaluation.

Integrating affection, emotion, and aesthetics into a General Theory of Learning

Every learning process is an affective experience. Affect is central in experiencing learning as uncertainty. This article proposes an internal integration of affect into the learning process. The main concepts of learning are articulated with a take on the reflection framework and a dynamic and social understanding of affection, emotions, and aesthetic experiences, helping to integrate concepts like edge-emotions and liminal experiences into the learning process. These concepts support the idea that complex emotions play a central part in learning dynamics, while arguing for reflection as a self-regulatory movement of the learning process. It is argued that there would be no such thing as a merely cognitive learning process. Every time that people learn, they experience edge-emotions and liminal experiences. Furthermore, if the learning process occurs in educational settings, it is possible to think about learning experiences as being mediated by liminal affective techniques and so, open to transformation.

Assessing the Proficiency and Factors Influencing Public High School Science Teachers’ Video Editing and Production Skills for Enhanced Instructional Presentations

In the rapidly evolving landscape of twenty-first-century education, the integration of contemporary digital technologies is pivotal for effective teaching. This research investigates the proficiency of public high school science teachers in video editing and production skills, particularly amidst the challenges posed by the ongoing pandemic. The study assesses attitudes, perceptions, and actual skills in video editing, identifying challenges and contributing insights for professional development. Aligned with the Cognitive Theory of Multimedia Learning and Generative Learning Theory, the research explores the advantages of multimedia in meaningful learning. While positive attitudes are evident, a significant gap in actual skills is revealed, varying with factors such as age, educational attainment, and length of service. Recommendations include targeted interventions, training programs, and equipping schools with digital tools to enhance science education through effective multimedia integration. Addressing these challenges is crucial for fostering a conducive learning environment,

Finding an answer in time: Assessing change in needs scores on time to recidivism among justice-involved youth

PurposeWhile risk instruments are consistently used to aid classification and supervision decisions, needs assessments guide intervention efforts for individuals under supervision. At the core of the Risk-Needs-Responsivity (RNR) model and the General Personality and Cognitive Social Learning (GPCSL) theory, dynamic needs scoring allows agencies to identify change in needs over time. Yet, few studies have assessed the potential impact of changes among needs items. To overcome this limitation, the current study assesses how needs score change may influence recidivism propensity among youth. MethodsUsing multi-level frailty models, the current study examines how changes in youth needs assessment scores influence time-to-recidivism among a large (N = 42,922), multi-state sample of justice-involved youth assessed with the Modified Positive Achievement Change Tool (MPACT). ResultsFindings demonstrate that youth with increased needs scores and those that remained the same at reassessment had a greater propensity for recidivism, compared to those that decreased scores. ConclusionsPolicy implications identify the effectiveness of the MPACT in measuring youth change, its utility for case management, and the needs domains most associated with recidivism reductions.

A case study on generative learning approaches in a studio and flipped class-room setting for increased learning outcomes

Teaching and learning during Covid-19 have been strongly affected by lockdowns, isolated online learning, and the sudden requirement to alternatively assess students while considering the effect internet-based information sources. Here, we present outcomes on the learning outcome of students returning from distance learning into the face-to-face mode, studying the subject “Embedded Mechatronic Systems” employing increasingly methods of Generative Learning Theory (GLT) in a flipped classroom environment, using studio and project-based learning approaches. By introducing a group project component, the formerly disconnected laboratory components become strongly connected with students being exposed to practical aspects and teamwork, generating reflected reports and videos of their practical work. To overcome the effects of Covi-d19, tighter assessments, and in-person engagements is emphasised. Viva-voces have been introduced and AI invigilated final exams have been altered to in-class room quizzes, while monitoring the cohort’s performance over 3 sessions. Our data indicate that face-to-face learning and hands-on practice with peers using self-testing and self-explaining strategies enacts higher outcomes, opposed to remote modes of teaching. Our results exemplify on how to move back into face-to-face teaching with future steps to increase learning outcomes using the flipped classroom, GLT, and a studio setting being discussed.

Collaborative generative learning activities in immersive virtual reality increase learning

Learning in immersive virtual reality (VR) can be highly motivating, but the perceptual richness and activity can distract students from the core instructional message. Generative learning activities may mitigate some of the limitations of immersive learning by helping learners focus on making sense of the key material. The main aim of this study was to examine whether learners benefit from being prompted to engage in individual or collaborative generative learning activities while immersed in a VR lesson compared to viewing the same lesson with no breaks. High school students (N = 164) viewed a biology lesson adapted for immersive VR about how our cells are structured and function. For the experimental conditions, the lesson was split up into four parts, with a pause after each part where learners summarized the main points and created a virtual representation of a cell; this was performed individually or collaboratively within the VR environment. Based on generative learning theory, we predicted that students engaging in individual and collaborative generative learning activities would display significantly higher posttest scores than the control group. Based on theories of computer-supported collaborative learning, we examined whether the collaborative generative activity group would achieve higher posttest scores than the individual generative activity group. The results showed that adding collaborative generative activities to a VR lesson was more effective at improving learning than adding individual generative activities. These results are consistent with collaborative cognitive load theory and demonstrate the value of adding collaborative generative learning activities to immersive VR lessons.

Task-dependent optimal representations for cerebellar learning.

The cerebellar granule cell layer has inspired numerous theoretical models of neural representations that support learned behaviors, beginning with the work of Marr and Albus. In these models, granule cells form a sparse, combinatorial encoding of diverse sensorimotor inputs. Such sparse representations are optimal for learning to discriminate random stimuli. However, recent observations of dense, low-dimensional activity across granule cells have called into question the role of sparse coding in these neurons. Here, we generalize theories of cerebellar learning to determine the optimal granule cell representation for tasks beyond random stimulus discrimination, including continuous input-output transformations as required for smooth motor control. We show that for such tasks, the optimal granule cell representation is substantially denser than predicted by classical theories. Our results provide a general theory of learning in cerebellum-like systems and suggest that optimal cerebellar representations are task-dependent.

Deriving a theory of learning from social movement practices

The field of Adult Education is rich with general theories of learning but limited in terms of theories that inform social movement learning (SML). Today, there are several conceptualizations of SML, but little learning theory development based directly on empirical studies of SML. This article aims to present findings from a systematic literature review of empirical studies on social movement learning (SML). We collected and identified 69 empirical studies focusing on adult learning and education within social movements for this literature review. We purposely focused on empirical research studies and did not include works that conceptualise or theorise social movement learning outside of actual empirical studies of SML. From our review of empirical studies, we have identified five elements we believe could serve as the foundation of a theory of learning and education in social movements.

Toward learning progression analytics — Developing learning environments for the automated analysis of learning using evidence centered design

National educational standards stress the importance of science and mathematics learning for today’s students. However, across disciplines, students frequently struggle to meet learning goals about core concepts like energy. Digital learning environments enhanced with artificial intelligence hold the promise to address this issue by providing individualized instruction and support for students at scale. Scaffolding and feedback, for example, are both most effective when tailored to students’ needs. Providing individualized instruction requires continuous assessment of students’ individual knowledge, abilities, and skills in a way that is meaningful for providing tailored support and planning further instruction. While continuously assessing individual students’ science and mathematics learning is challenging, intelligent tutoring systems show that it is feasible in principle. However, the learning environments in intelligent tutoring systems are typically not compatible with the vision of how effective K-12 science and mathematics learning looks like. This leads to the challenge of designing digital learning environments that allow for both – meaningful science and mathematics learning and the reliable and valid assessment of individual students’ learning. Today, digital devices such as tablets, laptops, or digital measurement systems increasingly enter science and mathematics classrooms. In consequence, students’ learning increasingly produces rich product and process data. Learning Analytics techniques can help to automatically analyze this data in order to obtain insights about individual students’ learning, drawing on general theories of learning and relative to established domain specific models of learning, i.e., learning progressions. We call this approach Learning Progression Analytics (LPA). In this manuscript, building of evidence-centered design (ECD), we develop a framework to guide the development of learning environments that provide meaningful learning activities and data for the automated analysis of individual students’ learning – the basis for LPA and scaling individualized instruction with artificial intelligence.

Generative Learning Strategies To Improve Students’ Cognitive Engagement In Online Classes At Islamic School: A Systematic Review

Purpose – This research aims to reveal learning strategies based on generative learning theory that have proven effective based on the results of empirical studies. This study was conducted by following the steps of systematic survey techniques in the social sciences. Design/methods/approach – The study was conducted by following the steps of systematic review techniques in the social sciences. There are seven steps in conducting a systematic review: formulating research questions, determining the type of research, conducting a comprehensive literature search, filtering literature search results, assessing studies that meet the criteria, synthesizing studies, and assessing heterogeneity between studies. Findings – This research shows how the learning process occurs in individuals based on generative learning theory. In addition, this study also reveals several learning strategies based on generative learning theory, including learning through summarizing, learning through mapping, learning through drawing, learning through imagining, and learning through teaching. Research Implications/Limitations – The results of this study can be used as a reference for teachers who want to implement learning strategies that can involve students’ cognitive aspects to produce more meaningful learning achievements. Originality/value – The results of this study provide educators with insight into how information processing occurs in a person’s cognition and uncover several learning strategies that align with information processing theory.

The Impact of Flipgrid in Students’ Learning Experience at Higher Learning Institution

Student-generated videos have been accepted as part of interactive learning activities in the classroom. The aim of this study is to provide insights into the impact of Flipgrid, which is an interactive social learning platform for student-generated videos, on students’ learning experience. The research design follows five principles of the Scholarship of Teaching and Learning (SoTL). This study focused on how students generate their own understanding of the concepts they learnt and shared through the Flipgrid application, using generative learning theory as its underlying foundation. A total number of 117 students who enrolled in the Accounting System Analysis and Design course in a university participated in this study. Data were collected using the students’ written reflections. The findings of this study revealed that the student-generated video through Flipgrid contributed to the positive students’ learning experience. In this regard, it boosted the confidence level, improved the understanding of the topic’s content, a fun learning activity, and others, such as improved students’ video editing skills. The outcomes offer insights into how Flipgrid can be used and beneficial for the learning activity.

Neurons learn by predicting future activity

Understanding how the brain learns may lead to machines with human-like intellectual capacities. It was previously proposed that the brain may operate on the principle of predictive coding. However, it is still not well understood how a predictive system could be implemented in the brain. Here we demonstrate that the ability of a single neuron to predict its future activity may provide an effective learning mechanism. Interestingly, this predictive learning rule can be derived from a metabolic principle, whereby neurons need to minimize their own synaptic activity (cost) while maximizing their impact on local blood supply by recruiting other neurons. We show how this mathematically derived learning rule can provide a theoretical connection between diverse types of brain-inspired algorithm, thus offering a step towards the development of a general theory of neuronal learning. We tested this predictive learning rule in neural network simulations and in data recorded from awake animals. Our results also suggest that spontaneous brain activity provides ‘training data’ for neurons to learn to predict cortical dynamics. Thus, the ability of a single neuron to minimize surprise—that is, the difference between actual and expected activity—could be an important missing element to understand computation in the brain.

Bilingual Abstract Semantic Associative Network Training (BAbSANT): A Polish-English case study

Introduction: This article presents a novel approach to anomia therapy (i.e., BAbSANT: Bilingual Abstract Semantic Associative Network Training) for bilingual persons with aphasia (B-PWA) that capitalizes both on lexico-semantic theories in bilingualism and general theories of semantic organization and learning. Based on previous work, we hypothesized that training abstract words in either language would promote within-language generalization, while training in the nondominant language would promote both within- and cross-language generalization.Methods: This case study used a single-subject A1BA2CA3 design. The participant was living with aphasia secondary to stroke and spoke both Polish and English, with Polish being his native and dominant language. Phase B consisted of abstract word training in Polish and phase C consisted of abstract word training in English. Prior to initiating therapy, in addition to a comprehensive language battery, we administered a cognitive control task to explore the relationship between cognitive control and treatment outcome.Results: We found within-language generalization regardless of the trained language, replicating previous work in monolingual persons with aphasia, further supporting the utility of training abstract words. However, contrary to our second hypothesis, cross-language generalization only occurred when the stronger language was trained.Conclusions: The discussion of the results of this case study is framed within previous work and theories of bilingualism. The lack of cross-language generalization when the weaker language was trained is discussed, taking into account nonverbal cognitive control deficits. In addition to showing the efficacy of BAbSANT, these results highlight the importance of considering cognitive control as a factor influencing therapeutic outcomes in anomia treatment in bilingual PWA.

Mediating the Low Verbal Intelligence–Early Adult Offending Relationship With Pro-Aggression Attitudes

This study was designed to explore a possible mechanism for the well-documented relationship between low verbal intelligence and early adult offending. It was hypothesized that low verbal intelligence, as measured by a brief vocabulary test, would predict higher pro-aggression thinking, which would then encourage future antisocial behavior. This hypothesis was tested in a longitudinal analysis of 411 male youths from the Cambridge Study of Delinquent Development (CSDD). After controlling for school performance, truancy, impulsivity, peer delinquency, and nonverbal intelligence, a path analysis revealed that low verbal intelligence at age 14 or 15 predicted violent offending (fighting) and property offending at age 21 or 22 by way of late adolescent pro-aggression attitudes. From these results, it was speculated that one mechanism linking low verbal intelligence to early adult offending is an attitude favorable to personal violation of the rights of others, in line with predictions from general personality and cognitive social learning (GPCSL) theory.

Benefits of interactive graphic organizers in online learning: Evidence for generative learning theory.

This study examined the impacts of 2 different graphic organizers (filled-in graphic organizers and interactive graphic organizers) on middle school students’ learning processes, outcomes, experiences, and preferences. In Experiment 1, 60 students were assigned to read a short expository passage in 1 of 3 conditions: text-only, filled-in graphic organizers, or interactive graphic organizers. Learning processes were examined with an eye-tracker that recorded students’ eye movements during learning. Learning outcomes were measured with retention and comprehension tests. Learning experiences were measured by survey instruments that probed students’ cognitive load and satisfaction. The results showed that compared to the text-only group, both graphic organizer groups performed better on retention and comprehension tests; spent less time fixating on the text area and more time on the graphic organizers area; and reported more learning satisfaction and less perceived difficulty. In addition, the interactive graphic organizers group performed better than the filled-in organizer group on comprehension tests and performed more up-down transitions and left-right transitions, indicating deeper processing. In Experiment 2, 230 students were asked to browse 54 materials with different graphic organizers and to select their favorite three materials. The results showed that the students preferred the interactive graphic organizers the most, then the filled-in graphic organizers, and the text-only last. These results support generative learning theory, suggesting that the interactive graphic organizers, which middle school students liked the most, encouraged them to engage in more integrative cognitive processes, achieve deeper learning outcomes, and have better learning experiences. (PsycInfo Database Record (c) 2021 APA, all rights reserved)

Generative learning strategies do not diminish primary students\u2019 attitudes towards augmented reality

Do generative learning strategies influence the motivational and affective factors of learning with augmented reality? This article explores this highly topical new question in the field of research on educational technology and reports the results of a value-added study that compares two mobile AR learning environments with or without additional learning strategies. A total of 56 primary school students participated and learned with augmented reality (AR) learning materials either in an experimental group or a control group. The experimental group learned with AR and additional learning strategies based on generative learning theory, namely, self-explanation and self-testing. The control group learned only with AR. It was investigated whether the addition of learning strategies would lead to a reduction in positive attitudes towards AR as a learning technology. The experimental group of students showed overall positive attitudes towards AR as a learning technology at approximately the same level as the control group. However, significant differences were found for the skepticism subscale, indicating that learners who learned with both AR and learning strategies were more skeptical about AR as a learning technology than those who learned only with AR. Gender differences were also found for the accessibility subscale, with male participants considering the AR technology to be easier to access outside of the classroom too. The impact of these results on theory and practice as well as further research directions is discussed.

Fit without fear: remarkable mathematical phenomena of deep learning through the prism of interpolation

In the past decade the mathematical theory of machine learning has lagged far behind the triumphs of deep neural networks on practical challenges. However, the gap between theory and practice is gradually starting to close. In this paper I will attempt to assemble some pieces of the remarkable and still incomplete mathematical mosaic emerging from the efforts to understand the foundations of deep learning. The two key themes will be interpolation and its sibling over-parametrization. Interpolation corresponds to fitting data, even noisy data, exactly. Over-parametrization enables interpolation and provides flexibility to select a suitable interpolating model.As we will see, just as a physical prism separates colours mixed within a ray of light, the figurative prism of interpolation helps to disentangle generalization and optimization properties within the complex picture of modern machine learning. This article is written in the belief and hope that clearer understanding of these issues will bring us a step closer towards a general theory of deep learning and machine learning.