Complex Learning Environments Research Articles

Service-Learning and Project-Based Learning Methodologies in Higher Music Education: a review of the literature

INTRODUCTION. Recent research highlights the potential of multidimensional and holistic learning in educational transforation, the provision of social services from the university and development of professional identity. This article aims to analyse the relationship between the Service-Learning and Project-Based Learning methodologies in higher music education and the acquisition of transversal competences. METHOD. A review of 29 articles on both methodologies in higher music education, published between 2012 and 2022, was conducted. The articles were selected from WoS, Scopus, and ERIC databases. Four categories were explored: (1) Social interaction, (2) personal growth, (3) academic learning, and (4) challenges related to the implementation and contextualization of the methodologies. RESULTS. Results show that, in the context of higher music education, both methodologies have a potentially positive impact on the development of transversal competencies in students. The review shows benefits in social aspects such as the development of civic responsibility and communication skills among peers and teachers; academic aspects such as adaptation to complex learning environments, mutually beneficial goals and shared authority; and personal development aspects such as flexibility, solidarity and respect. The review also shows that reflective practice contributes to developing students’ openness to constructive criticism, which is perceived as a positive contribution to learning. CONCLUSIONS. The methodologies studied can foster students’ personal growth, the mitigation of their biases in the classroom and the reflective and conscious appreciation of their own learning. To be taken into account are the challenges related to the complexity of adjusting the projects to the academic curriculum and community needs, as well as the large amount of time and effort required for the process. Finally, further research using different search terms and criteria is encouraged to achieve a broader understanding of how music initiatives can be designed and implemented through these methodologies, the projection they can have, and how research is conducted in this field.

Optimizing reinforcement learning in complex environments using neural networks

Optimizing reinforcement learning in complex environments using neural networks

Gaze cueing improves pattern recognition of histology learners.

Experts perceive and evaluate domain-specific visual information with high accuracy. In doing so, they exhibit eye movements referred to as "expert gaze" to rapidly focus on task-relevant areas. Using eye tracking, it is possible to record these implicit gaze patterns and present them to histology novice learners during training. This article presents a comprehensive evaluation of such expert gaze cueing on pattern recognition of medical students in histology. For this purpose, 53 students were randomized into two groups over eight histology sessions. The control group was presented with an instructional histology video featuring voice commentary. The gaze cueing group was presented the same video, but with an additional overlay of a live recording of the expert's eye movements. Afterward, students' pattern recognition was assessed through 20 image-based tasks (5 retention, 15 transfer) and their cognitive load with the Paas scale. Results showed that gaze cueing significantly outperformed the control group (p = 0.007; d = 0.40). This effect was evident for both, retention (p = 0.003) and transfer tasks (p = 0.046), and generalized across different histological contexts. The cognitive load was similar in both groups. In conclusion, gaze cueing helps histology novice learners to develop their pattern recognition skills, offering a promising method for histology education. Histology educators could benefit from this instructional strategy to provide new forms of attentional guidance to learners in visually complex learning environments.

The Effects of Complexity Leadership Theory on Organizational Learning in Complex Environments

The Effects of Complexity Leadership Theory on Organizational Learning in Complex Environments

Symposium 5: Design for networked learning: A case study in health science

Higher education (HE) institutions have been transforming dramatically since the pandemic started late 2019 and early 2020. After an initial period of emergency online teaching and learning, HE educators have focused our energy on supporting students' learning in a complex dynamic learning environment, where digital/online - material/physical - social elements are interwoven and interrelated. Networked learning can be a useful medium for us in this complex context. This paper explores a case study of design for networked learning in a health science postgraduate course. The course was designed in the context of a New Zealand university. The paper will examine how the course design reflects the eight principles of design for networked learning, and proposes some recommendations on design for networked learning at a course level. It links practice and theories, and illustrates how networked learning is unpacked in the context of the course design. While the current paper focuses on the design of the course, it is suggested that future research should conduct an evaluation of the design and develop empirical studies on students' and teacher's experience.

A Cognitive Load Theory Perspective of the Undergraduate Anesthesia Curricula in South Africa.

Safe anesthesia is indispensable to achieve global safe surgery and equitable health care access. The disease burden and lack of specialists in South Africa (SA) require junior, nonspecialist doctors to be fit-for-purpose from day 1 when they provide anesthetic services in peripheral hospitals with limited supervision. Graduating students report low self-perceived preparedness for administering anesthesia, but it is not known how their curricular experiences influence their learning. Cognitive load theory defines intrinsic, extraneous, and germane cognitive loads (subtypes). Intrinsic load relates to learning tasks, extraneous load to distractions, and germane load to students' learning processes. This study used a cognitive load theory lens to explore SA students' experiences of their undergraduate anesthesia training. In a constructivist cross-sectional descriptive study, we explored the qualitative factors that influenced students' curricular experience of undergraduate anesthesia training in SA. Two investigators analyzed the data independently in an initial coding round. An emerging theme of lack of time to achieve the expected outcomes, prompted the use of cognitive load theory as a conceptual framework for further analysis by the 3 authors. The subsequent analysis informed the development and refinement of a final cognitive load theory framework for anesthesia training, the COLOAD (COgnitive LOad in Anesthesia eDucation) framework. Data were collected between November 2017 and February 2019. The 1336 respondents (79% participation) reported a variety of determinants of learning pertaining to all 3 cognitive load subtypes. Participants were novices in an inherently complex environment and experienced a high cognitive load during anesthesia training. The number-, complexity-, and interactivity of tasks influenced intrinsic load, while extraneous load was affected by ineffective instructional methods, external- and internal distractors. Program design, metacognition, and learner motivation impacted germane load. Cognitive load theory provided a useful theoretical basis for understanding students' curricular experiences. The COLOAD framework suggests a microlevel interrelatedness of the constituting elements of the 3 cognitive load subtypes. This has implications for curriculum design, pedagogy, and student support. Learning outcomes development and curriculum mapping are important to ensure a lean curriculum, but measures to enhance germane cognitive load might be equally important to achieve competence. Attention to the hidden curriculum and active promotion of reflective practice might reduce cognitive load in complex learning environments such as anesthesia training.

An efficient and lightweight off-policy actor–critic reinforcement learning framework

In the framework of current off-policy actor–critic methods, the state–action pairs in an experience replay buffer (called historical behaviors) cannot be used to improve the policy, and the target network and the clipped double Q-learning techniques need to be used to evaluate the policy. The framework limits the policy learning capability in complex environments, and needs to maintain four critic networks. As a result, we propose an efficient and lightweight off-policy actor–critic (EL-AC) framework. In the policy improvement, an efficient off-policy likelihood ratio policy gradient algorithm with historical behaviors reusing (PG-HBR) is proposed, which promotes the agent to learn an approximately optimal policy by using the historical behaviors. Moreover, a theoretically interpretable universal critic network is designed. It can approximate the action-value and the state-value functions simultaneously, so as to obtain the advantage function in PG-HBR. In the policy evaluation, we develop the algorithms of low-pass filtering for target state-values and adaptive controlling algorithm for overestimation bias, which can evaluate the policy efficiently and accurately using only one universal critic network. Extensive evaluation results indicate that EL-AC outperforms the state-of-the-art off-policy actor–critic methods in terms of approximately optimal policy learning and neural network storage space occupation, and it is more suitable for policy learning in complex environments.

Knowledge-Enhanced Spatiotemporal Analysis for Anomaly Detection in Process Manufacturing

Effective fault detection and diagnosis (FDD) is crucial for proactively identifying irregular states that could jeopardize operator well-being and process integrity. In the era of Industry 4.0, data-driven FDD techniques have received particular attention, driven by the proliferation of stored manufacturing sensor data. While these methods have proven adept at categorizing established process fault scenarios, there remains an imperative to identify and explain anomalies stemming from uncharted faults or the interplay of consecutive anomalies. To address this we present a knowledge-enhanced FDD approach that integrates well-defined chemical engineering knowledge with cutting-edge deep learning techniques. We apply our methodology, named Knowledge-Enhanced Spatiotemporal Analysis (KESA), to identify abnormal process conditions that may be a precursor to failure. Furthermore, we utilize the knowledge of the fundamental relationships governing the process to explain why this fault case has occurred. This type of in-depth fault analysis is only possible through leveraging domain expertise and marks a step forward in FDD technology in comparison to current literature. Using the benchmark Tennessee Eastman process dataset, we establish superiority in the accuracy and efficiency of our KESA model against state-of-the-art FDD algorithms. This work highlights the importance of a knowledge-enhanced approach to deep learning in complex environments, emphasizing the critical role of timely and interpretable fault detection. By providing explanations for model results, our KESA framework not only aids in effective decision-making but also has the potential to significantly reduce the time between fault detection and the implementation of proactive mitigation actions. This capability is paramount for improving overall safety, minimizing downtime, and ultimately contributing to substantial cost savings in industrial processes.

Closing the loop by expanding the scope: using learning analytics within a pragmatic adaptive engagement with complex learning environments

Closing the loop by expanding the scope: using learning analytics within a pragmatic adaptive engagement with complex learning environments

Playing to learn: developing self-directed learning skills through serious games

Purpose Higher education is undergoing a significant transformation, demanding a rethinking of instructional methods, the establishment of novel assessment frameworks and the incorporation of state-of-the-art technologies to advance the development of learning competencies. The use of simulations is an alternative that offers satisfactory results and favors learning in new generations. This study aims to present a methodology for assessing the advancement of self-directed learning (SDL) in participants through simulation techniques and show that the incorporation of simulations can improve participants’ SDL skills. Design/methodology/approach This study uses a quantitative approach to evaluate the evolution of various competencies related to SDL among participants. Includes the application of scales specifically designed to measure readiness for SDL, the use of factor analysis to identify and validate essential factors and conducting hypothesis testing to verify shifts in students’ perceptions regarding the significance of SDL-related skills. Findings The findings of this study reveal a positive impact of simulations on the SDL readiness. Factor analysis identified five key factors: self-management skills, openness to learning opportunities, initiative and independence in learning, self-concept as an effective learner and desire for Learning. The use of simulations significantly improved critical thinking, logical reasoning, analysis and decision-making capabilities. These results demonstrate the effectiveness of this technique as a valuable tool for developing SDL skills and highlight the potential of such interventions in complex and uncertain learning environments. Research limitations/implications The study provided valuable insights into the impact of simulations in the logistics field, particularly in the development of SDL-related skills. There is a need for studies in other areas of knowledge that would allow for the generalization of these results. Likewise, it is advisable to use scales that measure the development of other types of skills. Additionally, the study’s focus on short-term effects may not fully capture the long-term development of SDL-related skills. Future research should address these limitations, expand the sample size, conduct longitudinal studies and explore possible contextual and external factors that may influence SDL outcomes in various educational settings, leading to broader and more robust conclusions. Practical implications The practical implications of this study are significant for both higher education institutions and educators in the logistics domain. The positive impact of the serious game on participants’ SDL skills highlights the potential of incorporating interactive and engaging learning tools in the curriculum. Educators can leverage serious games to foster critical thinking, logical reasoning and decision-making abilities in their students. Moreover, the identified key factors influencing SDL development provide valuable guidance for designing targeted interventions to enhance students’ self-management, initiative and love for learning. Social implications The social implications of this study underscore the importance of equipping individuals with SDL skills in a rapidly changing world. By integrating serious games and fostering SDL competencies, higher education institutions can contribute to a more adaptable and resilient workforce. Empowering students with critical thinking, innovative thinking and independent learning, they can enhance their ability to navigate the challenges of the labor market. This, in turn, may lead to a more informed and proactive society capable of addressing complex issues and making well-informed decisions. Originality/value This article arises from empirical exploration with students from two countries in Latin America (Mexico and Colombia), examining the importance of games in developing SDL skills. Furthermore, it promotes the use of a methodology with a low level of complexity, and that can be replicated with different games. This perspective adds valuable insights to the existing literature, offering practical implications for educators and institutions seeking effective strategies to promote SDL skills among students.

Traversing Situations and Contexts in Networked Learning

To meet the goals of business education and develop responsible business leaders, educators need to design networked learning environments that nurture and leverage connections. This includes connecting students to each other, their teachers, to industry and to the community. This paper aims to understand factors that support or inhibit students’ participation in networked learning in a business education context. Productive participation in learning networks is essential if students are to connect meaningfully with people and resources in ways that support their learning and experience. As the physical and digital learning environments students engage in often include complex configurations of tools, tasks, and epistemic resources, they require the skills and dispositions to effectively transition between these environments. Using a situated readiness framework by Hachmann and Dohn (2018), this study presents an analysis of focus group data from business students in higher education to identify ways in which students’ level of readiness impacts on their ability to participate effectively in learning networks. Students in the present study highlighted a range of challenges they faced when attempting to traverse between face-to-face and online learning environments. However, our study also revealed numerous other situations or contexts that business students needed to traverse as part of their networked learning experience. These were grouped into five overarching categories: domain; space and configuration; format, structure and resources; people or groups; and purpose and responsibility. Overlayed onto the situated readiness framework, these categories can be used by other researchers to gain a more nuanced understanding of how students navigate the complexities of networked learning environments. Future research conducted across a range of learning contexts would allow the categories to be refined and built upon. The study also identified skills and dispositions that contributed to students' level of readiness to navigate situations and contexts within networked learning environments, and some preliminary design considerations based on the findings. To support business students in higher education on their journey to becoming responsible business leaders, it is imperative that they are able to participate productively in complex networked learning environments. As educators, this requires us to understand their level of readiness to do so and equip them with the skills and dispositions they need to participate effectively.

The effectiveness of case method in developing intrapreneurship among business students

Intrapreneurship skill has considered as the alternative learning outcomes of entrepreneurship education. However, entrepreneurship teachers need a complex learning program to develop intrapreneurship among business students. At the same time, The Ministry of Education and Culture of The Republic of Indonesia recommends university teachers implement case methods to deliver complex learning environments and build critical skills among students. Therefore, this study aims to i) examine the effect of micro small medium enterprise (MSME) cases on the intrapreneurship of business students, ii) investigate the influence of MSME cases on flow experience in entrepreneurship education and iii) investigate the effect of flow experience during entrepreneurship education on intrapreneurship skill. We used field experiments on entrepreneurship and digital business student in business development courses. The result indicates that the case method effectively developed student intrapreneurship skill and flow experience during the course positively impacting student intrapreneurship skill.

Humans adaptively select different computational strategies in different learning environments.

The Rescorla-Wagner rule remains the most popular tool to describe human behavior in reinforcement learning tasks. Nevertheless, it cannot fit human learning in complex environments. Previous work proposed several hierarchical extensions of this learning rule. However, it remains unclear when a flat (nonhierarchical) versus a hierarchical strategy is adaptive, or when it is implemented by humans. To address this question, current work applies a nested modeling approach to evaluate multiple models in multiple reinforcement learning environments both computationally (which approach performs best) and empirically (which approach fits human data best). We consider 10 empirical data sets (N = 407) divided over three reinforcement learning environments. Our results demonstrate that different environments are best solved with different learning strategies; and that humans adaptively select the learning strategy that allows best performance. Specifically, while flat learning fitted best in less complex stable learning environments, humans employed more hierarchically complex models in more complex environments. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

How Do Operating Room Nurse Students Experience the Learning Environment in the Operating Room?

Please note this article was first published in Norwegian. You can read the Norwegian article here. Background: There is little research-based knowledge about how operating room nursing students experience the learning environment in an operating room. Results from international studies indicate that structural challenges such as time pressure, high demands for efficiency, and a minimum of time delegated to guidance are all characteristic of the learning environment. More insight into how operating room nursing students experience an operating room is an important element for improving the quality of practice studies in a high-tech and time-efficient environment. Aim: The purpose of the study is to describe operating room nursing students’ experiences of their learning environment in operating rooms. Method: The study has a qualitative and descriptive research design, utilizing systematic text condensation as an analytical method. Data was gathered through conducting focus-group interviews with operating room nursing students in their final semester of the nursing education study program. Results: Three main categories were brought up repeatedly by these students: 1) The significance of having supervisors, 2) The unclear responsibility with respect to formal and informal guidance in a multidisciplinary learning environment, and 3) The situation of learning in a complex and unpredictable learning environment. Conclusion: The results provide further insight into operating room nursing students’ experiences of their learning environment in authentic practice studies. The results can be utilized in further improving the learning environment for operating room nursing students.

Parallel executive pallio-motor loops in the pigeon brain.

A core component of the avian pallial cognitive network is the multimodal nidopallium caudolaterale (NCL) that is considered to be analogous to the mammalian prefrontal cortex (PFC). The NCL plays a key role in a multitude of executive tasks such as working memory, decision-making during navigation, and extinction learning in complex learning environments. Like the PFC, the NCL is positioned at the transition from ascending sensory to descending motor systems. For the latter, it sends descending premotor projections to the intermediate arcopallium (AI) and the medial striatum (MSt). To gain detailed insight into the organization of these projections, we conducted several retrograde and anterograde tracing experiments. First, we tested whether NCL neurons projecting to AI (NCLarco neurons) and MSt (NCLMSt neurons) are constituted by a single neuronal population with bifurcating neurons, or whether they form two distinct populations. Here, we found two distinct projection patterns to both target areas that were associated with different morphologies. Second, we revealed a weak topographic projection toward the medial and lateral striatum and a strong topographic projection toward AI with clearly distinguishable sensory termination fields. Third, we investigated the relationship between the descending NCL pathways to the arcopallium with those from the hyperpallium apicale, which harbors a second major descending pathway of the avian pallium. We embed our findings within a system of parallel pallio-motor loops that carry information from separate sensory modalities to different subpallial systems. Our results also provide insights into the evolution of the avian motor system from which, possibly, the song system has emerged.

Exploring the synergy between instructional design models and learning theories: A systematic literature review

To enhance education, we conducted a comprehensive investigation into integrating instructional design models (IDMs) and learning theories in this systematic literature review. We methodically selected and analyzed 25 publications from a pool of 1,102 documents using the preferred reportinfg items for systematic reviews and meta-analyses framework to guarantee a rigorous and systematic approach to literature selection. Our results demonstrate the worldwide span of study on this topic, including contributions from prestigious academic institutions and scholarly journals. This examination explores both the benefits and drawbacks of combining IDMs with learning theories. Noteworthy positives include increased student motivation, support for innovative teaching methods, and the development of complex and diverse learning environments. However, several shortcomings were observed. most notably relating to accessibility problems, evaluation difficulties, and questions about the adaptability of such integrated techniques. Our findings have implications for a broad range of stakeholders, including educators, instructional designers, and students functioning in a variety of educational contexts. The increase of learner motivation, the creation of novel pedagogical tools, the refining of teacher training programs, and the promotion of interdisciplinary learning methods are significant areas of focus. In addition, our evaluation uncovered a number of gaps in the current literature, indicating intriguing possibilities for future research. The examination of holistic learning environments, the untapped potential of integrated systems, the incorporation of educational robots into pedagogical tactics, and the refining of schema assessment approaches are notable research fields. By providing these insights, this systematic review not only adds to the current body of knowledge, but also has the potential to shape the future trajectory of educational practices, so acting as a significant resource for boosting learning outcomes in a variety of educational environments.

Rational inattention: A new theory of neurodivergent information seeking.

This paper presents rational inattention as a new, transdiagnostic theory of information seeking in neurodevelopmental conditions that have uneven cognitive and socio-emotional profiles, including developmental language disorder (DLD), dyslexia, dyscalculia and autism. Rational inattention holds that the optimal solution to minimizing epistemic uncertainty is to avoid imprecise information sources. The key theoretical contribution of this report is to endogenize imprecision, making it a function of the primary neurocognitive difficulties that have been invoked to explain neurodivergent phenotypes, including deficits in auditory perception, working memory, procedural learning and the social brain network. We argue that disengagement with information sources with low endogenous precision (e.g. speech in DLD, orthography-phonology mappings in dyslexia, numeric stimuli in dyscalculia and social signals in autism) constitutes resource-rational behaviour. We demonstrate the strength of this account in a series of computational simulations. In experiment 1, we simulate information seeking in artificial agents mimicking an array of neurodivergent phenotypes, which optimally explore a complex learning environment containing speech, text, numeric stimuli and social cues. In experiment 2, we simulate optimal information seeking in a cross-modal dual-task paradigm and qualitatively replicate empirical data from children with and without DLD. Across experiments, simulated agents' only aim was to maximally reduce epistemic uncertainty, with no difference in reward across information sources. We show that rational inattention emerges naturally in specific neurodivergent phenotypes as a function of low endogenous precision. For instance, an agent mimicking the DLD phenotype disengages with speech (and preferentially engages with alternative precise information sources) because endogenous imprecision renders speech not conducive to information gain. Because engagement is necessary for learning, simulation demonstrates how optimal information seeking may paradoxically contribute negatively to an already delayed learning trajectory in neurodivergent children. RESEARCH HIGHLIGHTS: We present the first comprehensive theory of information seeking in neurodivergent children to date, centred on the notion of rational inattention. We demonstrate the strength of this account in a series of computational simulations involving artificial agents mimicking specific neurodivergent phenotypes that optimally explore a complex learning environment containing speech, text, numeric stimuli, and social cues. We show how optimal information seeking may, paradoxically, contribute negatively to an already delayed learning trajectory in neurodivergent children. This report advances our understanding of the factors shaping short-term decision making and long-term learning in neurodivergent children.

Glocal Evaluation Competencies for Learning As We Go: Zooming in and zooming out to connect system-level solutions to local beneficiaries

Identifying essential competencies for evaluators has received significant attention in recent years yet practical examples of how to apply competencies to real-time learning in complex environments are lacking. In particular, the experience of those at the local level - ultimate beneficiary individuals (UBIs) - can get lost when evaluations take a systems perspective. Experienced evaluators share how Learning as we go is used to describe utilization-focused developmental evaluation embedding evaluative thinking and building capacity in public sector programs, that support learning and adaptation to improve the lives of those most impacted by inequitable and unsustainable global systems.

The quality of teaching behaviors in learning environments of DHH students.

Classrooms are complex learning environments, with instruction, climate, and teacher-student interactions playing important roles in students' academic progress. To investigate the learning environments of deaf and hard-of-hearing (DHH) students, we developed a new observational tool called the Quality of the Learning Environment-DHH rating scale (QLE-DHH) and rated 98 teachers of DHH students being educated in a range of classroom environments. The present study sought to (1) determine if the items on the QLE-DHH are good indicators of theoretically meaningful dimensions of classroom quality; (2) determine to what extent these dimensions predicted language and reading outcomes of DHH students; and (3) examine how teachers of DHH students were rated on the indicators of classroom quality. The findings suggested that the QLE-DHH has excellent structural validity. Ratings predicted student reading outcomes. Finally, the QLE-DHH was able to capture teachers' strengths and skills in need of improvement. The QLE-DHH appears to hold promise for use in both research and teacher preparation programs.

Measuring learning in digital games: Applying a game‐based assessment framework

Digital games (DGs) have the potential to immerse learners in simulated real‐world environments that foster contextualised and active learning experiences. These also offer opportunities for performance assessments by providing an environment for students to carry out tasks requiring the application of knowledge and skills learned in the classroom. Although widely used for teaching and learning, there are challenges in using digital game applications for assessment. Designing assessments around tasks in complex learning environments like DGs is not always easy, particularly for educators new to using these technologies for teaching. This paper presents a game‐based assessment framework (GBAF) that is designed to be educator‐friendly and useful for the design of assessments for immersive learning environments. The application of the framework to the design of embedded and external (multiple‐choice questions) assessments is also presented. The GBAF offered an easy and structured basis for the design of two distinct assessments for a computer game. It provides educators with useful guidelines for designing assessments around pre‐existing games. Practitioner notesWhat is already known about this topicImmersive technologies are increasingly being used for teaching and learning due to their benefits to knowledge and skills acquisition. However, for educators interested in using these tools for formal classroom teaching, there is a lack of resources and guidance on assessment designs and implementations. The most commonly used assessment design framework, the evidence‐centred design (ECD), is complicated to use, requiring advanced machine learning skills to implement. This has so far limited its use to large‐scale computerised and game‐based testing.What this paper addsThis paper presents a framework developed to guide educators through the design and implementation of assessments when teaching with immersive learning applications. Grounded in the constructive alignment principles and the ECD framework, the game‐based assessment framework is designed to help educators align assessment tasks to game tasks and the intended learning outcomes. It also provides step‐by‐step guidelines for the identification of appropriate immersive applications. It shows the practical application of the framework to the design of embedded (in‐game) assessments and external (multiple‐choice tests) assessments.Implications for practice and/or policyThe framework presented in this paper provides a structured and pedagogically sound basis for the design of assessments when measuring performance, or skills and knowledge acquisition with immersive learning applications.