HE METHOD OF COMBINED ONLINE ASSESSMENT ENGAGEMENT IN ADAPTIVE LEARNING SYSTEMS

Author(s):  
A. A. Voronina ◽  
O. A. Shabalina ◽  
A. V. Kataev

Modern trends in the development of educational software are associated with adaptive learning systems that can personalize the learning process. One of the key quality indicators of any learning system is user engagement in learning process. The known methods for assessing engagement of users of computer systems are based on collecting of various data on the user’s behavior, his emotional and neurophysiological state, etc., and interpreting it in the context of involvement. Confidence in the results of assessments based on interpretations may be insufficient to make decisions based on these results, which is of fundamental importance in case of using in adaptive learning systems. And besides not all the methods can be used online, which is a prerequisite for application in adaptive learning systems. A method for online assessing engagement has been developed, based on a combination of oculography, emotion analysis and web analytics methods, which is applicable for adapting the learning process in adaptive learning systems. The joint analysis of the physiological state and behavior (actions) of the user allows to take into account various aspects of the possible manifestation of the user engagement, and increase the confidence in the results of the assessment of engagement. Quantitative engagement indicators based on metrics applicable to online engagement assessment are suggested. Due to ambiguity of possible interpretations of quantitative indicators of involvement, a generalized assessment of engagement is determined using a fuzzy inference mechanism. To assess engagement a linguistic variable is used and a method for assessing user engagement is based on fuzzy rules. The proposed method is implemented in a web application that can be used to assess involvement online in adaptive learning systems. To set the linguistic variable for assessing engagement, an experiment will be conducted with the participation of users of learning systems and external experts. The values of the linguistic variable will be defined in such a way that the result of assessing involvement, obtained using the developed method, does not contradict the results of expert assessments.

2018 ◽  
Vol 19 (12) ◽  
pp. 1051-1054
Author(s):  
Lyudmyla Dzhuguryan

The article deals with the problems, disadvantages and advantages of using adaptive learning systems in interactive monitoring and assessment of knowledge. Methodical and technical aspects of interactive monitoring and assessment of knowledge based on the adaptive learning system are defined. The schemes of the algorithms based on which the learning process with simultaneous interactive monitoring and assessment of knowledge is realized is offered. Recommendations on the use of software products for the implementation of interactive monitoring and assessment of knowledge based on an adaptive learning system are proposed.


2020 ◽  
Vol 10 (1) ◽  
pp. 820-829
Author(s):  
Natasha Alyaa Anindyaputri ◽  
Rosihan Ari Yuana ◽  
Puspanda Hatta

AbstractThere have been some hindrances in the process of programming learning. An adaptive learning system, such as ELaC, Java Guide, and Java Grader provides an adaptable learning content that can accommodate the learning styles as well as preferences of each learning individual. Moreover, an adaptive learning system can help students of different capabilities in learning programming. This study examined the outcomes of the implementation of an adaptive learning system in programming learning, as well as some finding results that were conducted according to the Systematic Literature Review framework. The research questions of this research were: problems faced during learning of programming as a background of system development, advantages and disadvantages of the system characteristics, technology, features, and effectiveness of the developed adaptive learning system. This research produced concepts that are summed up upon the related resources. The results of this study summarized whether the use of adaptive learning systems in learning programming could overcome the problems encountered during the learning process.


2005 ◽  
Vol 2 (2) ◽  
pp. 99-114 ◽  
Author(s):  
Thierry Nabeth ◽  
Liana Razmerita ◽  
Albert Angehrn ◽  
Claudia Roda

This paper presents a cognitive multi-agents architecture called Intelligent Cognitive Agents (InCA) that was elaborated for the design of Intelligent Adaptive Learning Systems. The InCA architecture relies on a personal agent that is aware of the user's characteristics, and that coordinates the intervention of a set of expert cognitive agents (such as story telling agents, assessment agents, stimulation agents or help agents). This InCA architecture has been applied for the design of K"InCA, an e-learning system aimed at helping people to learn and adopt knowledge-sharing management practices.


2021 ◽  
Author(s):  
Alexander Olof Savi ◽  
Nick ten Broeke ◽  
Abe Dirk Hofman

Adaptive learning systems can be susceptible to between-subject cross-condition interference by design. This interference has important implications for the implementation and evaluation of A/B tests in such systems, as it obstructs causal inference and hurts external validity. We illustrate the problem in an Elo based adaptive learning system, discuss sources and degrees of interference, and provide solutions, using an example in the study of dropout.


Author(s):  
Y. B. Popova

The use of information technology and, in particular, learning management systems, increases the ability of both the teacher and the learner to achieve their goals in the educational process. Such systems provide educational content, help organize and monitor training, collect progress statistics, and can also take into account the individual characteristics of each user of the system. The purpose of this study is to determine the direction of development of modern learning systems and technologies for their implementation. The evolution of learning management systems, the transition to intelligent learning systems, the main stages of such systems were reviewed, the types of learning sequences were analyzed, the transformationinto adaptive learning systems was identified, and the scheme of the system and its mathematical model were presented. Expertise systems, the theory of fuzzy sets and fuzzy logic, cluster analysis, as well as genetic algorithms and artificial neural networks are defined as the mechanisms for implementing the learning systems. An artificial neural network in an adaptive learning system will allow you to create a unique training program that will build on existing knowledge and the level of perception of educational material by students. By formalizing the intellectual processes that both the teacher and the student carry out, it is possible to automate a certain part of the teacher’s functions, reduce the cost of manual labor, which will make it easier to monitor the learning process and also make the learning process more efficient.


2020 ◽  
Vol 166 ◽  
pp. 10015 ◽  
Author(s):  
Maiia Marienko ◽  
Yulia Nosenko ◽  
Alisa Sukhikh ◽  
Viktor Tataurov ◽  
Mariya Shyshkina

The article highlights the issues of personalized learning as the global trend of the modern ICTbased educational systems development. The notion, the main stages of evolution, the main features and principles of adaptive learning systems application for teachers’ training are outlined. It is emphasized that the use and elaboration of the adaptive cloud-based learning systems are essential to provide sustainable development of teachers’ education. The current trends and peculiarities of the cloud-based adaptive learning systems development and approach of their implementation for teachers’ training are considered. The general model of the adaptive cloud-based learning system structure is proposed. The main components of the model are described; the issues of tools and services selection are outlined. The methods of the cloudbased learning components introduction within the adaptive systems of teacher training are considered. The current research developments of modeling and implementation of the adaptive cloud-based systems are outlined.


2021 ◽  
pp. 545-558
Author(s):  
Angelina Voronina ◽  
Olga Shabalina ◽  
Alexander Kataev ◽  
Natalia Sadovnikova

2021 ◽  
Author(s):  
Thomas Wilschut ◽  
Florian Sense ◽  
Maarten van der Velde ◽  
Zafeirios Fountas ◽  
Sarah Maass ◽  
...  

Memorising vocabulary is an important aspect of formal foreign-language learning. Advances in cognitive psychology have led to the development of adaptive learning systems that make vocabulary learning more efficient. One way these computer-based systems optimize learning is by measuring learning performance in real time to create optimal repetition schedules for individual learners. While such adaptive learning systems have been successfully applied to word learning using keyboard-based input, they have thus far seen little application in spoken word learning. Here we present a system for adaptive, speech-based word learning using an adaptive model that was developed for and tested with typing-based word learning. We show that typing- and speech-based learning result in similar behavioral patterns that can be used to reliably estimate individual memory processes, and we extend earlier findings demonstrating that a response-time based adaptive learning system outperforms an accuracy-based, Leitner flashcard learning algorithm. In short, we show that adaptive learning benefits transfer from typing-based learning, to speech based learning. Our work provides a basis for the development of language learning applications that use real-time pronunciation assessment software to score the accuracy of the learner's pronunciations. The development of adaptive, speech-based learning applications is important for two reasons. First, by focusing on speech, the model can be applied for individuals whose typing skills are insufficient---as is demonstrated by the successful application of the model in an elderly participant population. Second, speech-based learning models are educationally relevant because they focus on what may be the most important aspect of language learning: to practice speech.


CCIT Journal ◽  
2014 ◽  
Vol 8 (1) ◽  
pp. 167-182
Author(s):  
Untung Rahardja ◽  
Sudaryono Sudaryono ◽  
Irwan Nurdin

The learning system is run in an educational institution, strongly influence the mindset and creativity of each student. In a learning system running on colleges Raharja, currently still using paper as a medium for performing tasks. The use of paper is a way of learning the manual and monotonous. To support that learning systems can be more interesting is to utilize existing information technology. iLearning is a method of lecturing in colleges Raharja who use the iPad as a media to facilitate the learning process of students. Given this method, students can learn, work, pray and play with iPad. The term is known as 4B. iLearning Media or shortened by the name iMe is a web application that is created and can be used by all students of colleges Raharja to explore their creativity in learning. This is an online learning system that facilitates student learning, because it can be done anywhere and anytime. It was concluded that the contribution of the iMe can be used as a medium of information for learning systems for the entire community colleges Raharja. Research methods used in conducting this research is the method of observation and literature


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