Transfer of learning in virtual environments: a new challenge?

The aim of all education is to apply what we learn in different contexts and to recognise and extend this learning to new situations. Virtual learning environments can be used to build skills. Recent research in cognitive psychology and education has shown that acquisitions are linked to the initial context. This provides a challenge for virtual reality in education or training. A brief overview of transfer issues highlights five main ideas: (1) the type of transfer enables the virtual environment (VE) to be classified according to what is learned; (2) the transfer process can create conditions within the VE to facilitate transfer of learning; (3) specific features of VR must match and comply with transfer of learning; (4) transfer can be used to assess a VE’s effectiveness; and (5) future research on transfer of learning must examine the singular context of learning. This paper discusses how new perspectives in cognitive psychology influence and promote transfer of learning through the use of VEs.     

A framework for process–solution analysis in collaborative learning environments

One of the most challenging aspects of computer-supported collaborative learning (CSCL) research is automation of collaboration and interaction analysis in order to understand and improve the learning processes. It is particularly necessary to look in more depth at the joint analysis of the collaborative process and its resulting product. In this article, we present a framework for comprehensive analysis in CSCL synchronous environments supporting a problem-solving approach to learning. This framework is based on an observation–abstraction–intervention analysis life-cycle and consists of a suite of analysis indicators, procedures for calculating indicators and a model of intervention based on indicators. Analysis indicators are used to represent the collaboration and knowledge building process at different levels of abstraction, and to characterize the solution built using models of the application domain, the problems to solve and their solutions. The analysis procedures combine analysis of actions and dialogue with analysis of the solution. In this way, the process and the solution are studied independently as well as together, enabling the detection of correlations between them. In order to exemplify and test the framework, the methodological process underlying the framework was followed to guide the implementation of the analysis subsystems of two existing CSCL environments. In addition, a number of studies have been conducted to evaluate the framework's approach, demonstrating that certain modes of collaborating and working imply particular types of solutions and vice versa.     

Simulation-based learning: The learning–forgetting–relearning process and impact of learning history

The results of empirical experiments evaluating the effectiveness and efficiency of the learning–forgetting–relearning process in a dynamic project management simulation environment are reported. Sixty-six graduate engineering students performed repetitive simulation-runs with a break period of several weeks between the runs. The students used a teaching tool called the project management trainer (PMT) that simulates a generic dynamic, stochastic project management environment. In this research, we focused on the effect of history recording mechanism on the learning forgetting process. Manual or automatic history recording mechanisms were used by the experimental group, while the control group did not use any history recording mechanism. The findings indicate that for the initial learning phase, the manual mechanism is better than the automatic mechanism. However, for the relearning phase, the break period length influenced the performance after the break. When the break period is short, the manual history keeping mechanism is better, but for a long period break, there is no significant difference. A comparison between the experimental group and the control group revealed that using any history recording mechanism reduced forgetting. Based on the findings, some practical implications of using simulators to improve the learning–forgetting process are discussed.     

Cognitive load theory vs. constructivist approaches: which best leads to efficient,deep learning?

Computer‐assisted learning, in the form of simulation‐based training, is heavily focused upon by the military. Because computer‐based learning offers highly portable, reusable, and cost‐efficient training options, the military has dedicated significant resources to the investigation of instructional strategies that improve learning efficiency within this environment. In order to identify efficient instructional strategies, this paper investigates the two major learning theories that dominate the recent literature on optimizing knowledge acquisition: cognitive load theory (CLT) and constructivism. According to CLT, instructional guidance that promotes efficient learning is most beneficial. Constructivist approaches, in contrast, emphasize the importance of developing a conceptual understanding of the learning material. Supporters of these theories have debated the merits and shortcomings of both positions. However, in the absence of consensus, instructional designers lack a well‐defined model for training complex skills in a rapid, efficient manner. The current study investigates the relative utility of CLT and constructivist‐based approaches for teaching complex skills using a military command and control task. Findings suggest that the acquisition of procedural, declarative, and conceptual knowledge, as well as decision‐making skills, did not differ as a function of the type of instruction used. However, integrated knowledge was slightly better retained by the group provided with CLT‐based instruction. These results are contrary to our expectation that constructivist approaches, which focus on the development and integration of information, would yield better performance in an applied problem‐based environment. Thus, while contemporary researchers continue to defend the use of constructivist strategies for teaching, our research supports earlier findings that question the utility, efficiency, and impact of these strategies in applied domains.     

Modelling and analysis of a rigid–compliant parallel mechanism

This paper presents a two-staged parallel mechanism composed by a rigid platform in a serial connection with a compliant platform, and concentrates on its configuration and interrelation. The analysis starts with the operator of a 3UPU configuration with a central strut being derived. Configuration and displacement formulas of the compliant platform are demonstrated, leading to the analytic equations of the relationship between the actuated angles of the operator and the position parameters of the end-effector. The numerical evaluation of workspace of the two-staged parallel mechanism is then followed.     

Pre-service teachers’ skills and perceptions about the use of virtual learning environments to improve teaching and learning

This paper explores data retrieved from Educational Immersive Virtual Worlds to describe pre-service teachers’ skills and perceptions about the simulation tasks. This project had 10 participants who were immersed for 3 years in the Technology and Pedagogical Models in Immersive Worlds island, a multi-user virtual environment in Second Life and Open Simulator. In this project, we evaluated how three-dimensional virtual environments can facilitate the achievement of teaching and learning processes. Based on quantitative and qualitative methodologies, two data collection instruments were applied. Through observation grids and personal log books, professional performance of the 18 pedagogical challenges implemented was collected. The statistical analysis shows that the students improved their technology skills and educational aspects about good practices in classes, regardless of the type of platform used. The analysis through Constant Comparing Method reported a positive assessment of the use of virtual environments, especially about the use of teaching strategies. Main conclusions regarding the pedagogical context reflect the importance of peer assessment on teaching performance, as well as the complexity of role-plays as intellectual challenges to enhance pre-service teachers’ skills. The main difficulties identified during the development of the activities were technical in nature, reporting hardware and connectivity issues.     

A quantitative multimodal discourse analysis of teaching and learning in a web-conferencing environment – The efficacy of student-centred learning designs

This paper presents a quantitative approach to multimodal discourse analysis for analyzing online collaborative learning. The coding framework draws together the fields of systemic functional linguistics and Activity Theory to analyze interactions between collaborative-, content- and technology-related discourse. The approach is used to examine how the task subject matter, the activity design, and the choice of interface affected interaction and collaboration for a computing course conducted in a web-conferencing environment. The analysis revealed the critical impact of activity design on the amount and type of discourse that transpired. Student-centred designs resulted in over six times more student discourse as compared to teacher-centred designs and created a learning environment where students took greater ownership over the tasks and contributed more to the content-based discussion. The paper also incorporates a rationale for the approach to coding and a reflection on its efficacy for discourse analysis in technology-based learning environments.     

Closed-loop analysis and control of a non-inverting buck–boost converter

In this article, a cascade controller is designed and analysed for a non-inverting buck–boost converter. The fast inner current loop uses sliding mode control. The slow outer voltage loop uses the proportional–integral (PI) control. Stability analysis and selection of PI gains are based on the nonlinear closed-loop error dynamics incorporating both the inner and outer loop controllers. The closed-loop system is proven to have a nonminimum phase structure. The voltage transient due to step changes of input voltage or resistance is predictable. The operating range of the reference voltage is discussed. The controller is validated by a simulation circuit. The simulation results show that the reference output voltage is well-tracked under system uncertainties or disturbances, confirming the validity of the proposed controller.     

Short- and long-term effects of students’ self-directed metacognitive prompts on navigation behavior and learning performance

This study seeks to promote learning in computer-based learning environments utilizing students’ self-directed metacognitive prompts. Such prompts are based on the idea of instructing students to design their own metacognitive scaffolds and learn with them afterward. In a pre-post experimental design, students in the experimental group (n = 35) were instructed to configure their own metacognitive prompts before learning whereas students in the control group (n = 35) learned without prompts. Log file analysis of navigation behavior indicates that students who learned with their individually designed, self-directed prompts visited relevant webpages significantly more often and spent a longer time on them compared with students in the control group. Moreover, participants in the experimental group attained better transfer performance immediately after learning. The long-term effect in transfer performance was even greater in a follow-up learning session conducted after three weeks without any instructional support in either group. These results are consistent with theories of metacognition and self-regulated learning and indicate that self-directed prompts can lead to sustainable effects.     

Explainable AI for domain experts: a post Hoc analysis of deep learning for defect classification of TFT–LCD panels

Journal of Intelligent Manufacturing - The deep learning (DL) model has performed successfully in various fields, including manufacturing. DL models for defect image data analysis in the...     

Developing a taxonomy of faculty participation in asynchronous learning environments—an exploratory investigation

Anecdotal evidence suggests that instructor performance in the online discussion portion of online courses has a major impact on learning and learner satisfaction. If this is the case, faculty development is an important component of success. This paper describes the development of a taxonomy of six categories to describe instructor postings to asynchronous discussions in online courses. This taxonomy was used during the inspection of 18 post-graduate level course sections at a Midwest university. The resulting data show that there is considerable variation in faculty teaching styles, interaction, and the amount of content-related feedback. The process also allowed issues such timeliness of feedback and responsiveness of faculty to be quantified. In-depth interviews with instructors and learners with experience of online courses were conducted to validate the qualitative data.     

Stability and bifurcation analysis for a model of a nonlinear coupled pitch–roll ship

Using a combination of analytical and numerical methods, the paper studies the stability and bifurcations for a model of a nonlinear coupled pitch–roll ship. The model represents a two-degree-of-freedom system with quadratic coupling subjected to a modulated sinusoidal excitation. Three types of critical points for the bifurcation response equations near the combination resonance in the presence of internal resonance are considered. These points are characterized by a double zero and two negative eigenvalues, a double zero and a pair of purely imaginary eigenvalues, and two pairs of purely imaginary eigenvalues, respectively. For each case, the stability regions for the initial equilibrium solution and the critical bifurcation curves are obtained. The amplitude response curves with respect to detuning/damping parameters for critical bifurcation parameters are obtained for the first two types, and detailed analyses of the eigenvalues of the linearized system for each parametric region are given. For the third type, with the aid of normal form theory, the explicit expressions of the critical bifurcation curves leading to incipient and secondary bifurcations are obtained. Bifurcations leading to 2D, 3D tori and their stability conditions are also investigated. Some new dynamical behaviors are presented for this system.     

Impact of hand-assisted viewing on user performance and?learning patterns in virtual environments

The ability to locate, select and interact with objects is fundamental to most Virtual Reality (VR) applications. Recently, it was demonstrated that the virtual hand metaphor, a technique commonly used for these tasks, can also be employed to control the virtual camera, resulting in improved performance and user evaluation in visual search tasks.     

Overall availability and risk analysis of a general robot–safety device system

We analyse the availability of a general robot–safety device system characterised by the feature of cold standby and by an admissible risky state. In contrast to the previous literature, we allow a general failure-free time distribution for the robot and, as an example, we present computational results for Coxian failure and repair time distributions. In order to decide whether the risky state is admissible, we introduce a risk criterion based on the notion of rare events. The criterion is always satisfied in the case of fast repair.     

Cognitive analysis of experts’ and novices’ concept mapping processes: An eye tracking study

The goal of this study was to explore how designated experts (subject experts with extensive experience in science education and concept mapping) and novices (pre-service teachers) establish concept map (CM) development processes while considering their cognitive processes. Two experiments were conducted in which eye-tracking, written, and verbal data were collected from 29 novices and 6 subject matter experts. The results showed that despite some similar strategies, novices and experts followed different patterns during the CM development process. Both experts and novices embraced deductive reasoning and preferred hierarchical type CMs. Additional points studied during the process include filling out requested information in different orders, branch construction pattern, content richness and progress pattern. Furthermore, eye behavior patterns also differed among experts and novices. Expert participants differed from novices in all eye behavior metrics (fixation count, fixation and visit duration for specific actions). Novices’ fixation count (FC) numbers were higher than the experts’ during the entire process and in specific periods. In conclusion, these pattern differences affect the CM development process directly. Considering the patterns revealed in the study may help instructors guide learners more adequately and effectively.     

Analysis and solution of a predator–protector–prey multi-robot system by a high-level reinforcement learning architecture and the adaptive systems theory

The area of competitive robotic systems usually leads to highly complicated strategies that must be achieved by complex learning architectures since analytic solutions are unpractical or completely unfeasible. In this work we design an experiment in order to study and validate a model about the complex phenomena of adaptation. In particular, we study a reinforcement learning problem that comprises a complex predator–protector–prey system composed by three different robots: a pure bio-mimetic reactive (in Brook’s sense, i.e. without reasoning and representation) predator-like robot, a protector-like robot with reinforcement learning capabilities and a pure bio-mimetic reactive prey-like robot. From the high-level point of view, we are interested in studying whether the Law of Adaptation is useful enough to model and explain the whole learning process occurring in this multi-robot system. From a low-level point of view, our interest is in the design of a learning system capable of solving such a complex competitive predator–protector–prey system optimally. We show how this learning problem can be addressed and solved effectively by means of a reinforcement learning setup that uses abstract actions to select a goal or target towards which a pure bio-mimetic reactive robot must navigate. The experimental results clearly show how the Law of Adaptation fits this complex learning system and that the proposed Reinforcement Learning setup is able to find an optimal policy to control the defender robot in its role of protecting the prey against the predator robot.     

Fuzzy min–max neural networks: a bibliometric and social network analysis

Neural Computing and Applications - The amount of digital data in the universe is growing at an exponential rate with the rapid development of digital information, and this reveals new machine...     

TD(λ) learning without eligibility traces: a theoretical analysis

A common approach to learning from delayed rewards is to use temporal difference (TD) methods for predicting future reinforcement values. They are parameterized by a recency factor λ which determines whether and how the outcomes from several consecutive time steps contribute to a single prediction update. TD(λ > 0) has been found to usually yield noticeably faster learning than TD(0), but its standard eligibility traces implementation is associated with some well known deficiencies, in particular significantly increased computation expense. This article investigates theoretically two possible ways of implementing TD(λ) without eligibility traces, both proposed by prior work. One is the TTD procedure, which efficiently approximates the effects of eligibility traces by the use of truncated TD(λ) returns. The other is experience replay, which relies on replaying TD prediction updates backwards in time. We provide novel theoretical results related to the former and present an original analysis of the effects of two variations of the latter. The ultimate effect of these investigations is a unified view of the apparently different computational techniques. This contributes to the TD(λ) research in general, by highlighting interesting relationships between several TD-based algorithms and facilitating their further analysis.