Systematic Review of Intelligent Tutoring Systems for Hard Skills Training in Virtual Reality Environments

Advances in immersive virtual reality (I-VR) technology have allowed for the development of I-VR learning environments (I-VRLEs) with increasing fidelity. When coupled with a sufficiently advanced computer tutor agent, such environments can facilitate asynchronous and self-regulated approaches to learning procedural skills in industrial settings. In this study, we performed a systematic review of published solutions involving the use of an intelligent tutoring system (ITS) to support hard skills training in an I-VRLE. For the seven solutions that qualified for the final analysis, we identified the learning context, the implemented system, as well as the perceptual, cognitive, and guidance features of the utilized tutoring agent. Generally, the I-VRLEs emulated realistic work environments or equipment. The solutions featured either embodied or embedded tutor agents. The agents’ perception was primarily based on either learner actions or learner progress. The agents’ guidance actions varied among the solutions, ranging from simple procedural hints to event interjections. Several agents were capable of answering certain specific questions. The cognition of the majority of agents represented variations on branched programming. A central limitation of all the solutions was that none of the reports detailed empirical studies conducted to compare the effectiveness of the developed training and tutoring solutions.Peer reviewe

The Multimodal Tutor: Adaptive Feedback from Multimodal Experiences

This doctoral thesis describes the journey of ideation, prototyping and empirical testing of the Multimodal Tutor, a system designed for providing digital feedback that supports psychomotor skills acquisition using learning and multimodal data capturing. The feedback is given in real-time with machine-driven assessment of the learner's task execution. The predictions are tailored by supervised machine learning models trained with human annotated samples. The main contributions of this thesis are: a literature survey on multimodal data for learning, a conceptual model (the Multimodal Learning Analytics Model), a technological framework (the Multimodal Pipeline), a data annotation tool (the Visual Inspection Tool) and a case study in Cardiopulmonary Resuscitation training (CPR Tutor). The CPR Tutor generates real-time, adaptive feedback using kinematic and myographic data and neural networks

Learning Path Construction in e-Learning – What to Learn and How to Learn?

Whether in traditional or e learning, it is important to consider: what to learn, how to learn, and how well students have learned. Since there are various types of students with different learning preferences, learning styles, and learning abilities, it is not easy to provide the best learning approach for a specific student. Designing learning contents for different students is very time consuming and tedious for teachers. No matter how the learning process is carried out, both teachers and students must be satisfied with students’ learning performance. Therefore, it is important to provide helpful teaching and learning guidance for teachers and students. In order to achieve this, we proposed a fined-grained outcome-based learning path model, which allows teachers to explicitly formulate learning activities as the learning units of a learning path. This allows teachers to formulate the assessment criteria related to the subject-specific knowledge and skills as well as generic skills, so that the pedagogy could be defined and properly incorporated. Apart from defining the pedagogical approaches, we also need to provide tailored learning contents of the courses, so that different types of students can better learn the knowledge according to their own learning abilities, knowledge backgrounds, etc. On the other hand, those learning contents should be well-structured, so that students can understand them. To achieve this, we have proposed a learning path generation method based on Association Link Network to automatically identify the relationships among different Web resources. This method makes use of the Web resources that can be freely obtained from the Web to form well-structured learning resources with proper sequences for delivery. Although the learning path defines what to learn and how to learn, we still needed to monitor student learning progress in order to determine proper learning contents and learning activities in an e-Learning system. To address the problem, we proposed the use of student progress indicators based on Fuzzy Cognitive Map to analyze both performance and non-performance attributes and their causal relationships. The aim is to help teachers improve their teaching approaches and help students reflect their strengths and weaknesses in learning. . This research focuses on the intelligent tutoring e-Learning system, which provides an intelligent approach to design and delivery learning activities in a learning path. Many experiments and comparative studies on both teachers and students have been carried out in order to evaluate the research of this PhD thesis. The results show that our research can effectively help teachers generate high quality learning paths, help students improve their learning performance, and offer both teachers and students a better understanding on student learning progress

iFocus: A Framework for Non-intrusive Assessment of Student Attention Level in Classrooms

The process of learning is not merely determined by what the instructor teaches, but also by how the student receives that information. An attentive student will naturally be more open to obtaining knowledge than a bored or frustrated student. In recent years, tools such as skin temperature measurements and body posture calculations have been developed for the purpose of determining a student\u27s affect, or emotional state of mind. However, measuring eye-gaze data is particularly noteworthy in that it can collect measurements non-intrusively, while also being relatively simple to set up and use. This paper details how data obtained from such an eye-tracker can be used to predict a student\u27s attention as a measure of affect over the course of a class. From this research, an accuracy of 77% was achieved using the Extreme Gradient Boosting technique of machine learning. The outcome indicates that eye-gaze can be indeed used as a basis for constructing a predictive model

Cognitive tutoring and assessment systems and mathematics achievement: a quantitative study of the Summit Learning Platform

Title from PDF of title page viewed June 16, 2021Dissertation advisor: Loyce CaruthersVitaIncludes bibliographical references (pages 151-191)Thesis (Ed.D.)--School of Education. University of Missouri--Kansas City, 2021The purpose of this study was to determine if the Summit Learning Platform, a type of Intelligent Tutoring System, has a positive association with mathematics achievement of high school students in grades nine through eleven. The study was conducted in a Midwest suburban school district among three high schools within the same district. Further, a quasi-experimental research design was used with a sample size of 2000 students in the control group and 450 students in the treatment group. Data were compiled from the 2018-2019 school year and applied a combination of t-tests and analysis of variance (ANOVA) to compare the mean scores of the two groups. As comparison points, the Northwest Evaluation Association (NWEA), pre-ACT, and ACT were used in this Midwest district as measures among all students. The results demonstrated that students using the Summit Learning Platform showed significant gains when using their pre-test and post-test scores, but there was not statistical significance when analyzing the measures between the control and treatment groups. As more school districts utilize technological tools in far-reaching efforts to raise achievement levels in math, the intent of the study was to demonstrate potential benefits of the Summit Learning Platform for districts across the nation.Introduction -- Review of literature -- Methodology -- Results of analyses and conclusions -- Discussio

An Adaptive E-Learning System based on Student’s Learning Styles and Knowledge Level

Es besteht eine starke Nachfrage nach einer positiven Applikation zum Lernen, um den strategischen Plan des indonesischen Ministeriums für Bildung und Kultur zu fördern, dass die Ratio von Berufsschule höher als die allgemeinbildende Schule werden kann. Die rasante entwicklung der Informations- und Kommunikationstechnologie könnte es ermöglichen, den Lernenden ein computergestütztes, personalisiertes E-Learning-System zur Verfügung zu stellen, um die Tatsache zu überwinden, dass jeder Lernende seine eigene Präferenz hat. Diese Studie bietet ein adaptives E-Learning-System, bei dem zwei Quellen der Personalisierung berücksichtigt werden: der Lernstil des Schülers und das Vorwissen. Um die Wirksamkeit des vorgeschlagenen E-Learning-Programms zu untersuchen, werden die Leistungen der Schüler bezüglich der drei niedrigsten Ebenen im kognitiven Bereich (Wissen, Verständnis und Anwendung) in der E-Learning-Gruppe mit denen der traditionellen Unterrichtsgruppe verglichen. Ein weiterer interessanter Bereich ist die sogannte schülerperspektive Usability-Bewertung und die Beziehung zwischen den Usability-Fragebogen angegebenen Aspekten zu erforschen. Der Entwurfs- und Entwicklungsprozess des adaptiven E-Learning-Systems in dieser Studie berücksichtigte sowohl das Instruktionsdesign als auch das Software-Engineering. Die erste Phase begann mit der Analyse des Kandidaten der Teilnehmer, des Fachkurses und des Online-Liefermediums. Der nächste Schritt bestand darin, die Prozedur, die Regelwerk der Adaptation und die Benutzeroberfläche zu entwerfen. Dann wurde Entwicklungsprozess des Lehrsystems auf der Grundlage der aus den vorherigen Phasen gesammelten Daten durchgeführt. Die nächste Phase war die Implementierung des Unterrichtsprogramms für die Schüler in einer kleinen Gruppe. Schließlich wurde die E-Learning-Anwendung in drei verschiedenen Teststrategien bewertet: Funktionsbasiertes Testen, Expertenbasierte Bewertung und benutzerperspektivische Bewertung. Die nächste Aktion ist eine experimentelle Studie, bei der das adaptive E-Learning-System im Lernprozess angewendet wird. An diesem Experiment waren zwei Gruppen beteiligt. Die Experimentalgruppe bestand aus 21 Studenten, die den Unterrichtsfach Digital Simulation mithilfe des adaptiven E-Learning-Systems lernten. Eine andere Gruppe war die Kontrollgruppe, die 21 Schüler umfasste, die dasselbe Unterrichtsfach in der traditionellen Klasse lernten. Es wurden zwei Instrumente verwendet, um die erforderlichen Daten zu erheben. Das erste Instrument bestand aus 30 Multiple-Choice-Fragen, die die kognitiven Ebenen von Wissen, Verstehen und Anwendung enthielten. Dieses Instrument wurde verwendet, um die Schülerleistung bei dem obengeschriebenen Unterrichtsfach zu bewerten. Das zweite Instrument war der Usability-Fragebogen, der aus 30 4-Punkte-Likert Aussagen bestand. Dieser Fragebogen bestand aus vier Dimensionen nämlich Nützlichkeit, Benutzerfreundlichkeit, Lernfreundlichkeit und Zufriedenheit. Mit diesem Fragebogen wurde die Usability der adaptiven E-Learning-Applikation basierend auf die Perspektive des Schülers bewertet. Der Befund dieser Studie ergab ein ungewöhnliches Phänomen, bei dem das Ergebnis des Pre-Tests der Kontrollgruppe signifikant höher als Experimentalgruppe. Zum Post-Test Vergleich, obwohl die Leistung der E-Learning Gruppe höher als der von der regulären war, war der Unterschied zwischen den beiden statistisch nicht signifikant. Der Vergleich der Punktzahlsteigerung wurde gemacht, um zu untersuchen, welche Behandlungsgruppe effektiver war. Die Ergebnisse zeigten, dass die gesamte Punktzahlsteigerung von der Experimentalgruppe signifikant höher als die von der Kontrollgruppe war. Diese Beweise waren auch im Hinblick auf das Wissen, das Verständnis und die Anwendungsebene des kognitiven Bereichs gültig. Diese Ergebnisse bestätigten, dass die Gruppe des adaptiven E-Learning-Systems bezüglich ihrer Leistung effektiver war als die Gruppe der Studenten, die in der traditionellen Klasse lernten. Ein weiterer wichtiger Befund betraf die Bewertung der Usability. Die Punktzahl der Messung wurde anhand verschiedener Ansätze analysiert und ergab, dass der Usability-Score in allen Aspekten (Nützlichkeit, Benutzerfreundlichkeit, Lernfreundlichkeit und Zufriedenheit) den akzeptablen Kriterien zuzuordnen ist. Darüber hinaus wurde die Regressionsanalyse durchgeführt, um die Beziehung zwischen den Variablen zu untersuchen. Der erste Befund ergab, dass die unabhängigen Variablen (Nützlichkeit, Benutzerfreundlichkeit und Lernfreundlichkeit) gleichzeitig die abhängige Variable (Zufriedenheit) beeinflussten. In der Zwischenzeit ergab der Teil t-Test unterschiedliche Ergebnisse. Die Ergebnisse zeigten, dass die variable Benutzerfreundlichkeit die variable Zufriedenheit signifikant beeinflusste. Der variable Nützlichkeit und die Lernfreundlichkeit wirkten sich indessen nicht signifikant auf die variable Zufriedenheit aus.There is a strong demand for a positive instructional application in order to address the strategic plan of the Ministry of Education and Culture in Indonesia to change the ratio of vocational secondary school to be higher than the general school one. The immense growth of information and communication technology may be possible to provide a computer-based personalized e-learning system to the learners in order to overcome the fact that each student has their own preferences in learning. This study offers an adaptive e-learning system by considering two sources of personalization: the student’s learning style and initial knowledge. In order to investigate the effectiveness of the proposed e-learning program, the students’ achievement in terms of three lowest levels in the cognitive domain (knowledge, comprehension, and application) in the e-learning group is compared with the traditional classroom group. Another area that is interesting to explore is the usability evaluation based on the students’ perspective and the relationship between aspects specified in the usability questionnaire. The design and development process of the adaptive e-learning system in this study was considering both the instructional system design and software engineering. The first phase was started by analyzing the participants’ candidate, the subject course, and the online delivery medium. The next step was designing the procedure, the adaptation set of rules, and the user interface. Then, the process to develop the instructional system based on the data collected from the previous phases was conducted. The next stage was implemented the instructional program to the students in a small group setting. Finally, the e-learning application was evaluated in three different settings: functional-based testing, experts-based assessment, and user-perspective evaluation. The next action is an experimental study by applying the adaptive e-learning system to the learning process. There were two groups involved in this experiment. The experimental group that consisted of 21 students who learned the Digital Simulation course by utilizing the adaptive e-learning system. Another group was the control group that included 21 students who studied the same course through the traditional classroom setting. There were two instruments used to collect the required data. The first instrument contained 30 multiple-choice questions that considered the cognitive levels of knowledge, comprehension, and application. This instrument was used to assess the student achievement of the intended course. The second instrument was the usability questionnaire that consisted of 30 4-point Likert scale statements. This questionnaire was composed of four dimensions, namely usefulness, ease of use, ease of learning, and satisfaction. This questionnaire aimed to evaluate the usability of the adaptive e-learning application based on the student’s perspective. The finding in this study revealed an unusual phenomenon which the pre-test result of the control group was significantly exceeding those of the experimental group. For the post-test score comparison, although there was a higher achievement in the e-learning group than in the regular group, the difference between both achievements was not statistically significant. The comparison in terms of the gain score was conducted in order to investigate which treatment group was more effective. The results indicated that the total gain score achieved by the experimental group was significantly higher than those recorded by the control group. This evidence was also valid with regard to the knowledge, comprehension, and application-level of the cognitive domain. These findings confirmed that the group who utilized the adaptive e-learning system was reported more effective in terms of the achievement score than the group of students who studied in the traditional setting. Another important finding was related to usability evaluation. The measurement score was analyzed through different approaches and revealed that the usability score categorized in the acceptable criteria in all aspects (usefulness, ease of use, ease of learning, and satisfaction). Furthermore, the regression analysis was conducted in order to explore the relation between the variables. The first finding reported that the independent variables (usefulness, ease of use, and ease of learning) simultaneously influenced the dependent variable (satisfaction). In the meantime, the partial t-Test found varying results. The results indicated that the variable ease of use was significantly influenced variable satisfaction. Meanwhile, variable usefulness and ease of learning were not significantly affected variable satisfaction

Augmented reality in clinical dental training and education

Dentistry is a profession that requires coordinated motor skills in addition to acquired knowledge for ideal execution of any treatment plan for patients. Learning experiences have been modified over a period of time for students as well as for the healthcare providers. Conventional pre-clinical training employed the use of cadavers, but financial, ethical and supervisory constraints have become a major shortcoming. With the adaptation of technology in dentistry, pre-clinical training has now employed simulation. It provides the opportunity for students to develop psychomotor skills for procedures by practising pre-clinical, standardised learning competencies before they engage in patient-management. Simulation involves computer-aided learning, augmented reality and virtual reality, which are largely taking over pre-clinical teaching. Augmented reality is commonly being employed in maxillofacial, restorative, tooth morphology learning and mastering technique for administering local anaesthesia in dentistry. Virtual reality is being employed particularly in pre-treatment implant planning and dental education for students. Use of haptic technology, like robotics, is also gaining popularity, and facilitates a two-way communication between the user and the environment to better simulate the clinical setting for learning purposes