Deep Learning Based Emotion Recognition and Visualization of Figural Representation

This exploration aims to study the emotion recognition of speech and graphic visualization of expressions of learners under the intelligent learning environment of the Internet. After comparing the performance of several neural network algorithms related to deep learning, an improved convolution neural network-Bi-directional Long Short-Term Memory (CNN-BiLSTM) algorithm is proposed, and a simulation experiment is conducted to verify the performance of this algorithm. The experimental results indicate that the Accuracy of CNN-BiLSTM algorithm reported here reaches 98.75%, which is at least 3.15% higher than that of other algorithms. Besides, the Recall is at least 7.13% higher than that of other algorithms, and the recognition rate is not less than 90%. Evidently, the improved CNN-BiLSTM algorithm can achieve good recognition results, and provide significant experimental reference for research on learners’ emotion recognition and graphic visualization of expressions in an intelligent learning environment.

LEARNER ACUMENS OF ONLINE EFL CLASSES AT THE PRIVATE UNIVERSITIES IN BANGLADESH

This study intended to evaluate the English as Foreign Language (EFL) learner responses to online classes during the covid-19 pandemic. It focused on the learner's insights rather than the teachers' views because the purpose is how the large population deals with technology during this pandemic. Though teachers are the real fighters, they are in a vacuum without the students' engagement. Therefore, this study showed EFL learners' readiness of using technology in attending online classes and what barriers they face during assessment and classes. It examined whether students can participate in group discussions, pair work, online assessment, respond to class, build their rapport, and get proper feedback or not. Data were collected randomly using a google form questionnaire having five elementary questions, fifteen Likert-type questions from 92 students of five private universities in Bangladesh. Besides, five questions were finally added to have an overview of multiple response analyses. Some imperative variables of flexibility, reliability, availability, and integrity regarding online classes were brought into light with descriptive analysis. Finally, the data were analysed in a qualitative approach. It shows that learners attending online courses and assessments are diverse regarding the availability of required facilities, and the students are having difficulties participating in online examinations. The result further implicates ensuring an intelligent learning environment in the 'new normal period' with more efficacy. <p> </p><p><strong> Article visualizations:</strong></p><p><img src="/-counters-/edu_01/0796/a.php" alt="Hit counter" /></p>

Development of an Integrated Complex of Knowledge Base and Tools of Expert Systems for Assessing Knowledge of Students in Mathematics within the Framework of a Hybrid Intelligent Learning Environment

The paper is devoted to the development of instrumental and methodological support for the assessment of students' knowledge in mathematics in the framework of a hybrid intellectual learning environment. According to the structural scheme of the model of intellectual assessment of knowledge and creative potential of students in mathematics, the structure of the corresponding knowledge base is formalized. Knowledge base within the framework of data mining methods to create a module for monitoring and evaluating knowledge in mathematics has been developed. To model the educational process the authors propose methods for solving clustering, dimensionality reduction, and classification problems based on machine learning and artificial neural networks. The basics for the development of integrated knowledge base complexes and artificial intelligence tools for the educational process are presented. The obtained results are aimed at creating methods which ensure the processes of operational training, control and evaluation of knowledge.

English Web-Based Teaching Supervision Based on Intelligent Face Image Perception and Processing for IoT

In this paper, the Internet of Things (IoT) with intelligent face perception and processing function is used to supervise online English teaching. In the intelligent learning environment, learners mainly learn by watching the information presentation screen of the learning content, i.e., the learning screen, which is the main environment for learners to learn and is the main channel for information interaction between learners and the learning content. The color matching, layout, graphic decoration, and background texture of the learning screen have a significant impact on learners’ emotions, interests, motivation, and effect in the learning process. On the contrary, the accurate identification of learners’ emotions is the basis for building a harmonious emotional interaction in the wisdom learning environment and is an important means to judge learners’ learning status, which is of great significance to promote learners’ wisdom learning. In addition to providing learners with personalized learning contents and learning paths, the learning images presented by the intelligent learning environment should also be compatible with learners’ emotional states and visual emotional preferences and can play a role in regulating and stimulating learners’ learning emotions. The system works well in the testing process, which verifies the feasibility, rationality, and effectiveness of our application of face perception to online teaching effectiveness monitoring, and can be combined with the old result-oriented effectiveness monitoring method for online teaching, with certain theoretical research significance and practical application value.

Implementation and Analysis of Intelligent Inquiry Teaching Model in Primary School English Teaching

As a linguistic discipline, the critical point of teaching English is to cultivate students’ comprehensive language application ability in listening, speaking, reading, and writing. Moreover, the cultivation of ability requires authentic linguistic context. The intelligent learning environment can provide a more authentic English situation in the intelligent inquiry teaching model and help students’ better familiar with communication methods. What is more, it attaches great importance to students’ learning process, such as discovery, induction, and evaluation, as a result, to promote and develop students’ intelligence. Based on intelligent inquiry teaching mode research, this article chose the E-book Bag as the learning environment. It focused on its improvement and application in primary school English teaching.

Intelligent learning environment for better student’s academic performance

In this paper, the authors aim to develop an intelligent learning environment model designed to improve students’ academic performance. Methodology: Referring to the litarature, the authors identified and analyzed a number of relevant issues that influence the specific components of an intelligent learning environment. These aspects were quantified using performance indicators defined on the basis of the specific objectives of each aspect chosen. Results: Following the analysis, the authors developed a model of intelligent learning space, and for its representation, we used conceptual modeling. Conclusions: Finally, the authors propose the prevalidation of the model using the dynamic modeling process and then the model will be piloted for final validation in both physical and virtual environment. These aspects are proposed because in the present study, the model was validated only based on the results from studies in scientific literature.

Learning Emotion Concepts

This paper reveals the importance of learning emotion concepts due to the efficiency of emotional granularity during the categorization of emotions. There are two ways of learning emotion concepts that can contribute to emotional granularity. First, we can learn emotion words. Second, we can learn the implicit content of our emotion concepts, i.e. how emotions feel to us. In order to complete the second task, we need to acquire vivid awareness and vivid memory of the implicit content of our emotion concept. I claim that only after completing the second task can we learn emotion words in a way that is efficient for the categorization of emotions. The problem with that claim is that we do not know how to study the implicit content of our emotions, and how to obtain vivid awareness of it. In this article, I sketch a basic solution to this problem. The article has three parts. In the first part, I outline Lisa Barrett’s Conceptual Act View in order to reveal the functional role of emotion concepts in our brains. In the second part, I explain Anna Wierzbicka’s classical attempt to define emotion concepts. In the third part, I suggest how it is possible to study the fine-grained details of our emotional experience in a scientific way. The goal of developing the integrative model is to realize the learner's potential in personalized knowledge formation in an intelligent learning environment and to enhance the efficiency of learning.

DEVELOPMENT OF INSTRUMENTAL AND METHODOLOGICAL SUPPORT FOR THE ASSESSMENT OF STUDENTS ' KNOWLEDGE IN MATHEMATICS IN THE FRAMEWORK OF HYBRID INTELLIGENT LEARNING ENVIRONMENT

The article is devoted to the development of an integrated complex of knowledge base and artifi-cial intelligence tools for assessing students' knowledge in mathematics within the framework of a hybrid intellectual learning environment. In accordance with the structural diagrams of mod-els of intellectual assessment of knowledge and creative potential of schoolchildren in mathe-matics, the structure of the corresponding knowledge base is formalized. The knowledge base is developed within the framework of data mining methods to create a module for monitoring and assessing knowledge in mathematics. As a methodological basis for the development of a knowledge base, the idea of V.P. Bespalko about the representation of the possible structure of human activity in the form of suc-cessive levels of assimilation, reflecting the development of the student's experience in a given subject in the learning process. The levels of assimilation (student, typical, heuristic, research) are determined through the ability to solve problems of the corresponding type. A formalized in-dicator of a student's achievement of a particular level of assimilation of educational material (level of training) is the coefficient of assimilation; assessment of the assimilation of material on a specific topic or section is provided for both at each of the above levels, and in general. The examples of the formation of a knowledge base for assessing the skills and abilities of schoolchildren in algebra are considered. To model the educational process, we propose methods for solving clustering, dimen-sionality reduction and classification problems based on machine learning and artificial neural networks. The foundations for the development of integrated complexes of knowledge bases and artificial intelligence tools to ensure the educational process are presented. The results obtained are aimed at creating methods that provide the processes of operational learning, control and assessment of knowledge, competencies and procedures, the level of formation of subject and professional competencies of students in the information and educational intellectual environment.

Κατασκευή εκπαιδευτικού, διαδραστικού, ψηφιακού περιβάλλοντος συνεργατικής αφήγησης πολλαπλών αναπαραστάσεων

Η αφήγηση αποτελεί την ραχοκοκαλιά της ανθρώπινης επικοινωνίας. Σε όλη την ιστορία της ανθρωπότητας γνώση για οποιοδήποτε αντικείμενο μεταδίδεται μέσω ιστοριών, ενώ σύνθετες έννοιες ή πληροφορίες γίνονται ευκολότερα κατανοητές μέσω της χρήσης τους. Τελευταία, ωστόσο, η αφήγηση έχει εμπλουτιστεί με τη συνέργεια των τεχνολογικών εξελίξεων δίνοντάς της μια νέα διάσταση, την ψηφιακή αφήγηση. Η ψηφιακή αφήγηση αποτελεί ισχυρό παιδαγωγικό εργαλείο για την τάξη του 21ου αιώνα αποτελώντας τεκμηριωμένα παράγοντα κλειδί στην εκπαιδευτική διαδικασία. Παρά το ότι μεγάλος αριθμός ερευνών εστιάζει στο σχεδιασμό και στη χρήση λογισμικών ψηφιακής αφήγησης, μοντέλα παιδαγωγικής αξιολόγησης και σχεδίασης λογισμικών ψηφιακής αφήγησης έως τώρα δεν έχουν αναφερθεί. Επιπλέον, λογισμικά εκπαιδευτικής ψηφιακής αφήγησης που πληρούν βασικές παιδαγωγικές προδιαγραφές σύμφωνα με τις σύγχρονες θεωρίες μάθησης και στοχεύουν στη διάγνωση και στο ξεπέρασμα των παρανοήσεων των μαθητών έως σήμερα δεν έχουν αναφερθεί από ερευνητές. Στο πλαίσιο του ερευνητικού πεδίου της Τεχνολογικά Υποστηριζόμενης Μάθησης μέσω Εκπαιδευτικών Ψηφιακών Αφηγήσεων, o σκοπός της παρούσας διδακτορικής διατριβής είναι τριπλός: (α) η δημιουργία ενός μοντέλου παιδαγωγικής αξιολόγησης εκπαιδευτικών λογισμικών ψηφιακής αφήγησης που θα περιλαμβάνει τα πλέον ουσιώδη παιδαγωγικά χαρακτηριστικά που πρέπει να έχει ένα εκπαιδευτικό λογισμικό ψηφιακής αφήγησης σύμφωνα με τις σύγχρονες προσεγγίσεις για τη γνώση και τη μάθηση, (β) η σχεδίαση και υλοποίηση ενός εκπαιδευτικού λογισμικού ψηφιακής αφήγησης που αφ ενός μεν θα καλύπτει όλες τις παιδαγωγικές διαστάσεις του μοντέλου αξιολόγησης εκπαιδευτικών λογισμικών ψηφιακών αφηγήσεων που προαναφέρθηκε με την μεγαλύτερη δυνατή πληρότητα και αφ ετέρου θα βοηθάει τους μαθητές στο ξεπέρασμα των παρανοήσεων που εντοπίστηκαν ότι έχουν, μέσω της δημιουργίας αλλά και παρακολούθησης εκπαιδευτικών ψηφιακών ιστοριών με θέμα τις έννοιες στις οποίες διαγνώστηκε ότι υπάρχουν παρανοήσεις μέσω των προσαρμοστικών λειτουργιών του λογισμικού, και (γ) η πιλοτική και διαμορφωτική αξιολόγηση του εκπαιδευτικού λογισμικού ψηφιακής αφήγησης από μαθητές και εκπαιδευτικούς με βάση το μοντέλο αξιολόγησης ψηφιακών αφηγήσεων που προαναφέρθηκε. Για την επίτευξη του σκοπού αυτού: (α) δημιουργήθηκε το μοντέλο αξιολόγησης εκπαιδευτικών λογισμικών ψηφιακής αφήγησης “Παιδαγωγικό Αστέρι Αξιολόγησης Ψηφιακής Αφήγησης” το οποίο περιλαμβάνει 16 παιδαγωγικές διαστάσεις, (β) σχεδιάστηκε και υλοποιήθηκε το εκπαιδευτικό περιβάλλον ψηφιακής αφήγησης S.M.I.L.E. (Storytelling based on students' Misconceptions Intelligent Learning Environment), και (γ) πραγματοποιήθηκε μια ενσωματωμένη μελέτη περίπτωσης (embedded case study) με 3 υπομονάδες (sub-units) ανάλυσης που αντιστοιχούν σε κάθε μια από τις 3 πιλοτικές εμπειρικές μελέτες που πραγματοποιήθηκαν (δύο σε μαθητές και μία σε εκπαιδευτικούς). Οι εμπειρικές αυτές μελέτες στόχο είχαν την πιλοτική αξιολόγηση του εκπαιδευτικού περιβάλλοντος ψηφιακής αφήγησης S.M.I.L.E.. Σύμφωνα με τα αποτελέσματα αυτής της πιλοτικής έρευνας, και λαμβάνοντας υπόψη τους περιορισμούς του δείγματος, κρίθηκε θετικά από μαθητές και εκπαιδευτικούς το εκπαιδευτικό περιβάλλον ψηφιακής αφήγησης S.M.I.L.E. όσον αφορά (i) στον εντοπισμό και στο ξεπέρασμα των παρανοήσεων των μαθητών, (ii) στην ανάπτυξη σημαντικών δεξιοτήτων και στάσεων των μαθητών μέσω της αλληλεπίδρασης με το λογισμικό, (iii) στην εξατομικευμένη αντιμετώπιση των μαθητών μέσω των ‘προσαρμοστικών’ λειτουργιών του λογισμικού, (iv) στη διαγραμματική αναπαράσταση της γνώσης -με εννοιολογικούς χάρτες- του αντικειμένου μάθησης των μαθητών από το λογισμικό, (iv) στη χρήση του μοντέλου ιστοριογράφησης Educational-W για την δημιουργία ψηφιακών ιστοριών μέσω του λογισμικού, και (v) στην ευχρηστία του λογισμικού. Αναμένεται ότι το “Παιδαγωγικό Αστέρι Αξιολόγησης Ψηφιακής Αφήγησης” που δημιουργήθηκε θα αποτελέσει ένα χρήσιμο εργαλείο αξιολόγησης και σχεδίασης εκπαιδευτικών λογισμικών ψηφιακών αφηγήσεων από εκπαιδευτικούς και ερευνητές με βάση τις σύγχρονες θεωρίες μάθησης. Επιπλέον, αναμένεται ότι το εκπαιδευτικό λογισμικό ψηφιακής αφήγησης S.M.I.L.E. θα χρησιμοποιηθεί από ερευνητές και εκπαιδευτικούς για τον εντοπισμό και το ξεπέρασμα των παρανοήσεων των μαθητών καθώς επίσης για τη δημιουργία σειράς σημαντικών και χρήσιμων δεξιοτήτων και στάσεων των μαθητών στον 21ο αιώνα.