Intelligent Tutoring Systems

Learning is a goal driven social activity determined by motivational factors. To be able to efficiently gamify learning for improved student motivation and engagement, the educators have to understand the related aspects studied in games, motivational psychology and pedagogy. This will help them to identify the factors that drive and explain desired learning behaviors. This paper presents a survey of the main approaches employed in gamification and the emerging new directions in the context of the relevant motivational psychology and pedagogy. The focus is on the motivational factors that impact learning and understanding of behavior change. The purpose of the paper is two-fold: on one side, to provide analysis and guide to relevant works related to gamification along with outlining the emerging trends, and on the other, to provide foundation for evaluation and identification of the areas of possible improvements.

The Hint Factory is a method of automatic hint generation that has been used to augment hints in a number of educational systems. Although the previous implementations were done in domains with largely deterministic environments, the methods are inherently useful in stochastic environments with uncertainty. In this work, we explore the game Connect Four as a simple domain to give decision support under uncertainty. We speculate how the implementation created could be extended to other domains including simulated learning environments and advanced navigational tasks.

Abstract. It has become standard practice to use the traditional information technologies such as web and email in education. But as the University campus becomes increasingly deployed with interconnected computing technology, we begin to ask how the resulting “iCampus” resource can be used in new and novel ways. This paper builds upon our previous work in the area of intelligent environments and goes beyond the typical use of computing technology within education. We report on our current research that aims to ...

A Web-based Intelligent Tutoring System is an educational platform that supports the teaching process with the aim of helping students navigate through the online course materials in order to achieve their learning goals. It has an ability to adapt an e-learning system to each individual learner according to his/her characteristics including the knowledge level, which usually come from uncertain information. Artificial intelligence techniques such as fuzzy logic and Bayesian networks are widely used to address uncertainty problems facing the intelligent tutoring systems. This research paper contributed to the field of research by developing an intelligent tutoring system, called FB-ITS using a combination of both the Bayesian network and fuzzy logic in order to support students in learning Excel. The system is validated and evaluated using an empirical method where the pre-test and post-test experiment was conducted in order to determine its effectiveness in providing learning to students. An experiment with 20 participants from undergraduate students yields positive results. It indicates that adapting learning material according to a knowledge level using a combination of Bayesian and fuzzy logic leads to better learning performance than using only the Bayesian network.

This thesis presents work on analytical reasoning with external representations (ERs) using problems similar to those used in the US GRE college-entrance examination. The work investigates the factors associated with effective ER use in situations where subjects select, construct and reason with their own ERs. Practically all previous work has tended to focus solely upon performance rather than process. In this thesis the emphasis is upon cognitive processes during the entire time-course of reasoning with ERs, from problem comprehension through to answer selection. A background to the work is provided by 2 comprehensive reviews of: 1.)  previous research on ERs and reasoning and 2.) the cognitive and semantic properties of ERs.

Results from three empirical studies are reported.  The first study examined a large corpus of `workscratchings' produced by subjects as they solved paper and pencil-based analytical reasoning problems under test conditions.  The workscratching ERs showed great diversity between and within subjects and across a range of problems. They included lists, various kinds of table, set diagrams, node and arc diagrams, first-order and propositional logic, plans and natural language.  It is shown that problem-solving performance is related to the type of ER used in the solution.

The second study utilised a computer-based system (switchERI). The system administered analytical reasoning problems and provided a range of ER construction environments for the subject to choose and switch between. User-system interactions were recorded dynamically during problem solving. This methodology permitted micro-analyses of the cognitive events at each stage during the time-course of problem solving. A process account of analytical reasoning with ERs is developed in which five major stages are identified - problem comprehension, ER selection, ER construction, read-off from the ER and answer selection/responding. A range of common slips and misconceptions are identified at each stage.  The results show, inter alia, that subjects whose responses are consistent with their ERs perform better than subjects whose responses are inconsistent with their ERs \textit{even if the ER is partially incorrect\/}.

The data from the workscratching analysis and {switchERI study informed the design of switchERII, a second system. SwitchERII incorporates a representation of the semantics of Euler's Circles, dynamically parses the user's representation and provides feedback and advice. A third study was conducted with the switchERII system.

Few, if any, studies to date have attempted to relate subjects' prior knowledge of ER formalisms to their reasoning performance.  Subjects' prior knowledge of ER formalisms was assessed in both switchER studies. It was observed that subjects' performance on representation interpretation tasks does not necessarily predict their performance in conditions where they select and construct their own representations. The reasons for the decoupling are discussed.

Data from all three studies show that subjects often utilise multiple representations in their solutions, either concurrently or serially via ER switching.  Two distinctly different types of switching were observed.  One kind (`thrashing') is associated with poorer performance and reflects less comprehensive prior knowledge, inability to select an appropriate ER and hazy problem comprehension.  Judicious switching, on the other hand, is associated with high levels of problem comprehension and skilled matching of the ERs' properties to changing task demands.

It is claimed that effective reasoning with ERs involves complex interactions between at least three factors: (a.)  within-subject variables such as the subject's representational repertoire (prior knowledge) and representational modality preferences (cognitive style); (b.) skill at overcoming a variety of barriers to comprehension and an ability to discern the salient attributes and characteristics of different problem types and (c.) an understanding of the semantic and cognitive properties of graphical and non-graphical ERs coupled with an ability to match those properties to the problem's task demands.  It is suggested that the role of externalisation in reasoning with ERs may be to facilitate the swapping of information between cognitive subsystems. A mechanism by which the use of diagrammatic ERs may facilitate self-explanation is also proposed.

The thesis concludes with an argument in favour of a domain-independent
`ER curriculum' . It is suggested that direct instruction in the use of a range of ERs might equip students with wider representational repertoires and hence allow them more scope to indulge their representational preferences. Finally, several directions for future work are proposed. These include extending the representational semantics of switchERII, evaluating various types of system feedback and implementing a mechanism for checking for slips during read-off from ERs.

E-Assessment which is also known as technology-enhanced assessment or online assessment is the continuous electronic assessment process where information and communication technology is used for the presentation of assessment activity, and the recording of responses. E-Assessment offers both teachers and students new possibilities for interacting in an immersive and responsive educational environment, moving beyond the static environment of the traditional pen and paper approach. E-Assessment is an emerging concept and it has become increasingly attractive in Higher Education. This paper presents a literature review of the e-assessment along the dimensions of its key elements, systems, tools, and approaches, with special emphasis on the assessment of both skills and knowledge. These dimensions can provide theory and technology which are useful for designing and developing an e-assessment system for skill and knowledge acquisition in an online course.

The idea of digital game-based learning (DGBL) is gaining acceptance among researchers, game designers, educators, parents, and students alike. Building new educational games that meet educational goals without sacrificing what makes games engaging remains largely unrealized, however. If we are to build the next generation of learning games, we must recognize that while digital games might be new, the theory and technologies we need to create DGBL has been evolving in multiple disciplines for the last 30 years. This chapter will describe an approach, based on theories and technologies in education, instructional design, artificial intelligence, and cognitive psychology, that will help us build intelligent learning games (ILGs).

In this paper we propose the architecture of an Intelligent Tutoring
System that considers the student's learning style and the competency-based education. We also describe the processes that have been implemented so far.
Our architecture presents innovations in the representation of the tutor module and in the knowledge module. Especially, the tutor module incorporates a selector agent, which will choose the content to show, considering the teaching strategies that support the student's learning style.

Online learning often requires learners to be self-directed and engaged. The present study examined students’ self-regulatory behaviors in online video-based learning environments. Using an experimental design, this study investigated the effects of a newly designed enhanced video learning environment, which was designed to support or scaffold students’ self-regulated or self-directed learning on students’ learning behaviors and outcomes. In addition, correspondence between students’ self-regulation strategies in traditional learning environments and observed self-regulated learning behaviors in the enhanced video environment were examined. A cross-sectional experimental research design with systematic random assignment of participants to either the control condition (common video) or the experimental condition (enhanced video) was utilized. Undergraduate and graduate students participated in the study (N = 80). Study results indicate that the newly designed enhanced video learning environment was a superior instructional tool than the common video learning environment in terms students’ learning performance. In addition, there was correspondence between graduate students’ self-reported self-regulation and observed self-regulation, with those high on seeking/learning information and managing their environment/behavior more likely to engage more in interactive note-taking.

Purpose. Tarticle aims to substantiate the conceptual principles of preparing future teachers for tutoring activities in the information and communication educational environment accordingly to the current state and trends of social development and education. Methodology. The scientific methods of analysis, generalization, description and comparison have been used in order to determine the conceptual framework to preparing future teachers for tutoring. Findings. The article presents the author’s concept of training teachers to be for the tutoring activity in the informational and computer
educational environment of a higher educational institution. The legal provisions of the Concept, its main idea, the theoretical (laws, regularities, didactic principles) and methodological (approaches, purposes, tasks, organizational and pedagogical conditions) as the basis for training teachers to be for the tutoring activity are highlighted. Originality. The peculiarity of this training is that the teacher, who has the tutor competence, can perform tutorial functions while working with students and, at the same time, be the leader and the organizer of the tutorial activity for teachers of other subjects. Therefore, the training teachers for tutoring activity should include two vectors: the first is to be aimed at preparing for tutoring with students in the course for professional activity (realization of an individual approach in educational
and school process), while the another is aimed at preparing for the organization of educational and informational pedagogical community to the purpose of carrying out the tuition supporting students. Practical value. The research results can be used at preparing educational programs for the training of tutors by providers of educational services. This material will be interesting for the researchers in the fields of theory and methodology for professional education, tutoring, training to teacher. Conclusions. Training teachers to be for the tutoring activity in the Concept is presented as the gradual formation of general and professional competences for the teachers to be in a rich informational and computer education environment by means of studying the expedient content, application at a complex of forms, methods, means
and technologies of teaching tutor activity, oriented tasks (exercises). The Concept is based on such methodological approaches as anthropological, individual, person-oriented, systematic, activity-based, competence-based, resourcebased, modular, and interdisciplinary ones. The author defines the ways of professional training for future teachers of tutoring: gradual, professional and scientific-professional training, informal and informal education.

This chapter reviews instructional methods (techniques, strategies, and tactics) in the literature used to promote positive affective states resulting in the acquisition of “robust” knowledge and skill develop- ment; mitigate negative affective states, which inhibit learning; enhance and maintain learner engagement to maximize opportunities for learning; and support the development of learner perseverance or grit. For purposes of our discussion, an instructional technique is a domain-independent and largely learner- independent method used in either human- or computer-based tutoring. In other words, the technique is implemented within an ITS as a method that has been shown to have positive effect on learning across training and educational domains, and across a variety of learners and learner states and traits. Instruc- tional techniques are best practices developed over time and include, but are not limited to error-sensitive feedback, mastery learning, adaptive spacing and repetition, metacognitive prompting, and faded worked examples. Generalized instructional techniques are discussed later in this chapter.

Access to relevant and accurate information is at the heart of tourism, more so in this era of the Internet information overload has become a prevalent phenomenon and as such a serious issue for those seeking for appropriate information. Furthermore, various researches have been carried out on how to make information on tourism website more effective. Intelligent tourism management system tries to bridge the gap by noting what a tourist perceives as relevant, in terms of content pertaining to tourism products in tourism websites. This study focuses mainly on content because it is seen as the key factor associated with an effective website. Hence, the aim of this research entails the design and implementation of an intelligent platform that will assist tourists in gaining access to information on tourist locations in Nigeria. In view of the forgoing, the system was implemented using Rational Unified Process as the adopted software development process, whereas MySQL, HTML and PHP were...

Intelligent Tutoring Systems (ITS) are computer programs that model learners’ psychological states to provide individualized instruction. They have been developed for diverse subject areas (e.g., algebra, medicine, law, reading) to help learners acquire domain-specific, cognitive and metacognitive knowledge. A meta-analysis was conducted on research that compared the outcomes from students learning from ITS to those learning from non-ITS learning environments. The meta-analysis examined how effect sizes varied with type of ITS, type of comparison treatment received by learners, type of learning outcome, whether knowledge to be learned was procedural or declarative, and other factors. After a search of major bibliographic databases, 107 effect sizes involving 14,321 participants were extracted and analyzed. The use of ITS was associated with greater achievement in comparison with teacher-led, large-group instruction (g = .42), non-ITS computer-based instruction (g = .57), and textbooks or workbooks (g = .35). There was no significant difference between learning from ITS and learning from individualized human tutoring (g = –.11) or small-group instruction (g = .05). Significant, positive mean effect sizes were found regardless of whether the ITS was used as the principal means of instruction, a supplement to teacher-led instruction, an integral component of teacher-led instruction, or an aid to homework. Significant, positive effect sizes were found at all levels of education, in almost all subject domains evaluated, and whether or not the ITS provided feedback or modeled student misconceptions. The claim that ITS are relatively effective tools for learning is consistent with our analysis of potential publication bias.

A pesar que los Sistemas Tutores Inteligentes tienen el propósito de guiar al alumno en el proceso de enseñanza-aprendizaje, actualmente se busca que sean más versátiles y centrados en
la forma en que los alumnos prefieren procesar la información. Es por esto que en el presente documento se aborda esta problemática, implementando un modelo de estilo de aprendizaje en un Sistema Tutor Inteligente.

Access to relevant and accurate information is at the heart of tourism, more so in this era of the Internet information overload has become a prevalent phenomenon and as such a serious issue for those seeking for appropriate information. Furthermore, various researches have been carried out on how to make information on tourism website more effective. Intelligent tourism management system tries to bridge the gap by noting what a tourist perceives as relevant, in terms of content pertaining to tourism products in tourism websites. This study focuses mainly on content because it is seen as the key factor associated with an effective website. Hence, the aim of this research entails the design and implementation of an intelligent platform that will assist tourists in gaining access to information on tourist locations in Nigeria. In view of the forgoing, the system was implemented using Rational Unified Process as the adopted software development process, whereas MySQL, HTML and PHP were the implementation tools used in the development of the system. Upon completion, the system was able to provide information by fetching information from the web pertaining to the subject of interest to assist tourists in decision making process. It was also able to act intelligently by using hybrid recommendation technique to recommend tourist locations based on their preference.

Inquire Biology is a prototype of a
new kind of intelligent textbook — one
that answers students’ questions,
engages their interest, and improves
their understanding. Inquire Biology
provides unique capabilities through a
knowledge representation that captures
conceptual knowledge from the textbook
and uses inference procedures to answer
students’ questions. Students ask questions
by typing free-form natural language
queries or by selecting passages of
text. The system then attempts to
answer the question and also generates
suggested questions related to the query
or selection. The questions supported by
the system were chosen to be educationally
useful, for example: what is the
structure of X? compare X and Y? how
does X relate to Y? In user studies, students
found this question-answering
capability to be extremely useful while
reading and while doing problem solving.
In an initial controlled experiment,
community college students using the
Inquire Biology prototype outperformed
students using either a hard copy or conventional
ebook version of the same
biology textbook. While additional
research is needed to fully develop
Inquire Biology, the initial prototype
clearly demonstrates the promise of
applying knowledge representation and
question-answering technology to electronic
textbooks.

In this paper we present a technique that employ Artificial Neural Networks and expert systems to obtain knowledge for the learner model in the Linear Programming Intelligent Tutoring System(LP-ITS) to be able to determine the academic performance level of the learners in order to offer him/her the proper difficulty level of linear programming problems to solve. LP-ITS uses Feed forward Back-propagation algorithm to be trained with a group of learners data to predict their academic performance. Furthermore, LP-ITS uses an Expert System to decide the proper difficulty level that is suitable with the predicted academic performance of the learner. Several tests have been carried out to examine adherence to real time data. The accuracy of predicting the performance of the learners is very high and thus states that the
Artificial Neural Network is skilled enough to make suitable predictions.

One of the challenges faced by most lecturers who teach English as a Second Language (ESL) is in marking or grading of students’ essays. Apart from being an overwhelming task, there is a need for lecturers to maintain consistency in marking. Some studies have shown that although they are given the same scoring rubrics, lecturers may give different grades to the same essay. The reason for this is due tothe fact that, most of the scoring rubrics mark essays holistically. One alternative in order to avoid the confusion is by marking analytically. In this paper, we describe a technique that can be used totransform holistic marking scoring rubrics into equivalent rubrics for analytic marking. This technique firstly identifies the dimensions of writing in holistic scoring rubrics based on Cohen (1994:307). Then,it refines these dimensions into their corresponding attributes. These attributes can be measured quantitatively and the grade of a particular essay is calculated by using mathematical formulae, which is based on a predefined marking scheme. This information serves as some of the software requirements for a CBEM (Computer Based Essay Marking) system for Malaysian ESL learners at IHLs (Institutions of Higher Learning) in Malaysia.

With the rapid growth of technology, computer learning has become
increasingly integrated with artificial intelligence techniques in order to
develop more personalized educational systems. These systems are
known as Intelligent Tutoring systems (ITSs). This paper focused on the
variant characteristics of ITSs developed across different educational
fields. The original studies from 2007 to 2017 were extracted from the
PubMed, ProQuest, Scopus, Google scholar, Embase, Cochrane, and Web
of Science databases. Finally, 53 papers were included in the study
based on inclusion criteria. The educational fields in the ITSs were
mainly computer sciences (37.73%). Action-condition rule-based
reasoning, data mining, and Bayesian network with 33.96%, 22.64%, and
20.75% frequency respectively, were the most frequent artificial
intelligent techniques applied in the ITSs. These techniques enable ITSs
to deliver adaptive guidance and instruction, evaluate learners, define
and update the learner’s model, and classify or cluster learners.
Specifically, the performance of the system, learner’s performance, and
experiences were used for evaluation of ITSs. Most ITSs were designed
for web user interfaces. Although these systems could facilitate
reasoning in the learning process, these systems have rarely been
applied in experimental courses including problem-solving, decisionmaking
in physics, chemistry, and clinical fields. Due to the important
role of a cell phone in facilitating personalized learning and given the
low rate of using mobile-based ITSs, this study has recommended the
development and evaluation of mobile-based ITSs.