Evaluation of an adaptive and intelligent educational hypermedia for enhanced individual learning of mathematics: A qualitative study

The purpose of this study is to design a personalized adaptive and intelligent web based tutoring system based on learning style and expert system named UZWEBMAT and to evaluate its effects on 10th grade students’ learning of the unit of probability. In the study, initially, learning objects were prepared in three different ways in relation to three sub-learning areas of Visual–Auditory–Kinesthetic (VAK) learning style for each subject of the probability unit. These were appropriate for secondary school mathematics curricula. Then, they were transferred into the digital environment. Each student’s dominant learning style determines the content to which s/he will be directed since s/he is directed to the content that is appropriate for his/her learning style. The course to be followed by the students within UZWEBMAT and their browsing around the pages are decided by expert system integrated into the system. This expert system sets the situations in which s/he will get solution supports and the course s/he will follow in accordance with the performance of the student. Hereby, each student may follow a different course, and the solution supports s/he will get may also differ highlighting the individual learning. The sample of the study consists of 81 10th grade students and 3 mathematics teachers from two high schools in Trabzon, Turkey. Qualitative data were obtained both from the teachers and students participating in the study in order to answer the research questions about the implementation and evaluation of UZWEBMAT for mathematics teaching in a high school classroom. Obtained data were analyzed using qualitative data analysis methods. According to the results of the present study, positive opinions of students and teachers such as taking into account the individual learning differences and deriving mathematical relations and formulas through exploration became prominent. In addition, there were also other positive opinions of students and teachers such as providing permanent learning and introducing learning responsibility to the students. In this sense, it was concluded that UZWEBMAT is a beneficial instrument for both students and teachers.     

The effects of UZWEBMAT on the probability unit achievement of Turkish eleventh grade students and the reasons for such effects

This study aimed at determining the effects of UZWEBMAT (Turkish abbreviation of Adaptive and INtelligent WEB based MAThematics teaching–learning system) on the probability unit academic achievement of students and the underlying reasons for these effects. The study was conducted in an Anatolian High School located in a district of Trabzon province, Turkey in the fall semester of the academic year 2011–2012. The research sample consisted of 106 eleventh grade students and 2 mathematics teachers. Semi-experimental method was used in the study. Pre-Probability Unit Achievement Test (pre-PUAT), Post-Probability Unit Achievement Test (post-PUAT), Scale for Evaluation of the UZWEBMAT by Students (SEUS), Student Interview Form (SIF), and Teacher Interview Form (TIF) were used for collecting data. Research results indicated that there was a statistically significant difference in favor of the experimental group (EG) students between the academic achievement of the EG students and that of the control group (CG) students. In addition, male EG students were found to be more successful than female EG students. However, no statistically significant relationship was found between the learning styles and the academic achievements of the EG students with different learning styles (visual–auditory–kinesthetic). In addition, no statistically significant relationship was detected between the genders and the academic achievements of the EG students having different learning styles. It was concluded that the higher achievement of the EG students resulted from the fact that they received education in accordance with their learning styles via UZWEBMAT, the learning objects included in UZWEBMAT had appropriate structural characteristics, students enjoyed learning in that environment, and students had continuous interest in the lesson.     

Design and development of an innovative individualized adaptive and intelligent e-learning system for teaching–learning of probability unit: Details of UZWEBMAT

In this study, an innovative adaptive and intelligent web based e-learning system, UZWEBMAT (Turkish abbreviation of Adaptive and INtelligent WEB based MAThematics teaching–learning system) was designed, developed and implemented. This e-learning system was intended for learning and teaching secondary school level permutation-combination-binomial expansion and probability subjects. Content which was prepared according to Turkish curriculum for secondary school mathematics course was transformed into learning objects in three different ways in accordance with VAK (Visual–Auditory–Kinesthetic) learning styles. Primary/secondary/tertiary learning styles of learners registering the system are determined and each learner receives the content appropriate for his/her dominant learning style. Also, they can be directed to contents of other styles according to their performances thanks to an expert system. Learning objects constituting the content were prepared according to constructivist approach. An active role for the learner was the purpose. Tips and intelligent solution supports within the learning objects were presented with expert system support to the learners. With this structure, UZWEBMAT bears the characteristics of intelligent tutoring system as well as an adaptive e-learning environment. All the movements of learners studying with UZWEBMAT are recorded and the necessary information is reported to both learners and teachers in a visualized way.     

Effects of teaching and learning styles on students’ reflection levels for ubiquitous learning

Ubiquitous learning (u-learning), in conjunction with supports from the digital world, is recognized as an effective approach for situating students in real-world learning environments. Earlier studies concerning u-learning have mainly focused on investigating the learning attitudes and learning achievements of students, while the causations such as learning style and teaching style were usually ignored. This study aims to investigate the effects of teaching styles and learning styles on reflection levels of students within the context of u-learning. In particular, we investigated the teaching styles at the dimensions of brainstorming and instruction and recall and the learning styles at the dimensions of active and reflective learning. The experiment was conducted with 39 fifth grader students at an elementary school in southern Taiwan. A u-learning environment was established at a butterfly ecology garden to conduct experiments for natural science courses. The experimental results of one-way ANCOVA show that those students who received a matching teaching–learning style presented a significant improvement in their reflection level. That is, matching the learning styles of students with the appropriate teaching styles can significantly improve students’ reflection levels in a u-learning environment.     

A drawing and multi-representational computer environment for beginners’ learning of programming using C: Design and pilot formative evaluation

This paper presents both the design and the pilot formative evaluation study of a computer-based problem-solving environment (named LECGO: Learning Environment for programming using C using Geometrical Objects) for the learning of computer programming using C by beginners. In its design, constructivist and social learning theories were taken into account. The general design has taken into consideration models of the learning process and subject matter as well as potential learner behaviour in dealing with fundamental tasks. The main emphasis has been placed on the role of: (a) multiple external representations in student learning, (b) motivation, through performing problem-solving activities taken from the familiar and meaningful context of drawing, using simple geometrical objects, (c) the active participation of students in their own learning by using hands-on experience, (d) appropriate feedback on the actions taken by students, to aid their self-correction, and (e) holistic, activity-based, multi-media, multi-representational and multi-layered content for the learning of basic concepts of programming using C. LECGO was pilot evaluated in the field through a qualitative and comparative study where nine 12th grade (18-year-old) students participated. In fact, students faced three similar yet not identical sets of four tasks across three learning environments, namely; paper and pencil (p–p), Turbo C and LECGO. The data emerging from this field evaluation study indicates that students gain better results within LECGO than in both the p–p environment and the typical programming environment of Turbo C, while performing similar activities.     

Learning style Identifier: Improving the precision of learning style identification through computational intelligence algorithms

Identifying students’ learning styles has several benefits such as making students aware of their strengths and weaknesses when it comes to learning and the possibility to personalize their learning environment to their learning styles. While there exist learning style questionnaires for identifying a student's learning style, such questionnaires have several disadvantages and therefore, research has been conducted on automatically identifying learning styles from students’ behavior in a learning environment. Current approaches to automatically identify learning styles have an average precision between 66% and 77%, which shows the need for improvements in order to use such automatic approaches reliably in learning environments. In this paper, four computational intelligence algorithms (artificial neural network, genetic algorithm, ant colony system and particle swarm optimization) have been investigated with respect to their potential to improve the precision of automatic learning style identification. Each algorithm was evaluated with data from 75 students. The artificial neural network shows the most promising results with an average precision of 80.7%, followed by particle swarm optimization with an average precision of 79.1%. Improving the precision of automatic learning style identification allows more students to benefit from more accurate information about their learning styles as well as more accurate personalization towards accommodating their learning styles in a learning environment. Furthermore, teachers can have a better understanding of their students and be able to provide more appropriate interventions.     

Designing learner-controlled educational interactions based on learning/cognitive style and learner behaviour

Recently, research in individual differences and in particular, learning and cognitive style, has been used as a basis to consider learner preferences in a web-based educational context. Modelling style in a web-based learning environment demands that developers build a specific framework describing how to design a variety of options for learners with different approaches to learning. In this paper two representative examples of educational systems, Flexi-OLM and INSPIRE, that provide learners a variety of options designed according to specific style categorisations, are presented. Experimental results from two empirical studies performed on the systems to investigate learners' learning and cognitive style, and preferences during interaction, are described. It was found that learners do have a preference regarding their interaction, but no obvious link between style and approaches offered, was detected. Derived from an examination of this experimental data, we suggest that while style information can be used to inform the design of learning environments that accommodate learners' individual differences, it would be wise to recommend interactions based on learners' behaviour. Learning environments should allow learners or learners' interaction behaviour to select or trigger the appropriate approach for the particular learner in the specific context. Alternative approaches towards these directions are also discussed.     

Learning styles' recognition in e-learning environments with feed-forward neural networks

Abstract People have unique ways of learning, which may greatly affect the learning process and, therefore, its outcome. In order to be effective, e-learning systems should be capable of adapting the content of courses to the individual characteristics of students. In this regard, some educational systems have proposed the use of questionnaires for determining a student learning style; and then adapting their behaviour according to the students' styles. However, the use of questionnaires is shown to be not only a time-consuming investment but also an unreliable method for acquiring learning style characterisations. In this paper, we present an approach to recognize automatically the learning styles of individual students according to the actions that he or she has performed in an e-learning environment. This recognition technique is based upon feed-forward neural networks.     

Effects of the application of graphing calculator on students’ probability achievement

A Graphing Calculator (GC) is one of the most portable and affordable technology in mathematics education. It quickens the mechanical procedure in solving mathematical problems and creates a highly interactive learning environment, which makes learning a seemingly difficult subject, easy. Since research on the use of GCs for the teaching and learning of probability in institutions of higher learning appears to be limited, a study was conducted to examine the effects of the use of GCs on students’ performance in probability. The study involved 65 pre-university students in a private institution of higher learning in Malaysia. Hypothesis testing showed that there is a significant difference in the mean score of the post achievement test between the experimental and control groups. Students in the experimental group displayed higher achievement than their peers in the control group in the Probability Achievement Test (PAT). Findings also showed that the use of GCs benefits students of all levels, that is, high, average and low mathematics achievers. Qualitative data provides a more lucid picture of how GCs aid in improving understanding and performance. Recommendations made will provide researchers, policy-makers and educators an alternative means of enhancing the quality of probability education.     

Fostering collective and individual learning through knowledge building

The purpose of this study was to design and examine a computer-supported knowledge-building environment and to investigate both collective knowledge-building dynamics and individual learning in the context of a tertiary education course in mainland China. The participants were 102 students in four intact Year-one tertiary business classes. Two classes experienced a knowledge-building environment (CKB) and the other two were taught using a regular project-based approach (RPBL). Data were obtained from interactions in the forum, writing quality, group-learning portfolios, and surveys. Quantitative analyses indicated that the knowledge-building groups outperformed the comparison groups on academic literacy assessed in terms of conceptual understanding and explanation, and obtained higher scores on beliefs about collaboration. Within-group analyses indicated that the students’ engagement in Knowledge Forum was a significant predictor of their academic literacy. Qualitative contrastive analyses of high- and low-performance groups identified different patterns of conceptual, metacognitive and social processes, and showed that student groups engaging in more collective and meta-discourse discourse moves performed better on individual scores in academic literacy. The implications of examining both collaborative dynamics and individual learning and designing computer-supported knowledge building for tertiary students are discussed.     

Implement web learning environment based on data mining

The need for providing learners with web-based learning content that match their accessibility needs and preferences, as well as providing ways to match learning content to user’s devices has been identified as an important issue in accessible educational environment. For a web-based open and dynamic learning environment, personalized support for learners becomes more important. In order to achieve optimal efficiency in a learning process, individual learner’s cognitive learning style should be taken into account. Due to different types of learners using these systems, it is necessary to provide them with an individualized learning support system. However, the design and development of web-based learning environments for people with special abilities has been addressed so far by the development of hypermedia and multimedia based on educational content. In this paper a framework of individual web-based learning system is presented by focusing on learner’s cognitive learning process, learning pattern and activities, as well as the technology support needed. Based on the learner-centered mode and cognitive learning theory, we demonstrate an online course design and development that supports the students with the learning flexibility and the adaptability. The proposed framework utilizes data mining algorithm for representing and extracting a dynamic learning process and learning pattern to support students’ deep learning, efficient tutoring and collaboration in web-based learning environment. And experiments do prove that it is feasible to use the method to develop an individual web-based learning system, which is valuable for further study in more depth.     

The effectiveness of using procedural scaffoldings in a paper-plus-smartphone collaborative learning context

The purpose of this study was to evaluate the effectiveness of using procedural scaffoldings in fostering students’ group discourse levels and learning outcomes in a paper-plus-smartphone collaborative learning context. All participants used built-in camera smartphones to learn new knowledge by scanning Quick Response (QR) codes, a type of two-dimensional barcode, embedded in paper-based learning materials in this study. Sixty undergraduate and graduate students enrolled at a four-year university in southern Taiwan participated in this study. Participants were randomly assigned into two different groups, using procedural scaffoldings learning and non-procedural scaffoldings learning. The learning unit about the Long Tail, an important concept used in products sales, was the learning task that participants were expected to complete. During the experiment, pretest–posttest and the completed group worksheets were used to collect data. The researchers applied content analyses, chi-square test, t-test, and ANCOVA to answer research questions. The findings indicated that participants in the experimental group using procedural scaffoldings achieved better learning outcomes than their counterparts in the control group in terms of group discourse levels, group learning, and individual learning.     

Analyzing collaborative interactions: divergence,shared understanding and construction of knowledge

One of the most important facets of collaborative learning is the interaction between individual and collaborative learning activities – between divergent perspectives and shared knowledge building. Individuals bring divergent ideas into a collaborative environment. While individuals bring their own unique knowledge and perspectives, the second important aspect of collaborative learning is how they move from seemingly divergent perspectives to collaborative knowledge building. This is clearly a social process among group members who could adopt various strategies for resolving differences including asserting dominance, acquiescing, or some form of reciprocal sense making. An important aspect of collaborative learning is the move from assimilation to construction, i.e., creating new understandings based on the discussions that they have had. Documenting this change from divergence to collaborative knowledge building to possible construction is therefore important in understanding the nature the collaborative interactions. In this paper we discuss our analysis of the process of collaborative interactions based on three dimensions – divergence of ideas, collaborative knowledge building and construction. Our aim was to document as well as to understand how collaborative interactions develop over time: whether students raise new issues (ideas) more frequently as they become more familiar with the discussion and discussants, and whether shared knowledge building becomes richer over time, and subsequent evidence that students were able to construct their own understanding based on their interactions with others. Our analyses were conducted in the context of an online graduate course conducted using the learning environment that we designed, CoDE, (Constructivist, Distributed learning Environment). In this paper, we will first describe the design of CoDE. We will then describe a study in which CoDE was used to offer an online graduate course in learning theories. We then discuss our analyses of both individual and collaborative learning as it progressed through the duration of the course.     

基于学习风格的自适应式虚拟交互方法的研究

新工科教育的改革推进了自适应学习的发展,以往的自适应方式对学习者的主观能动性的重视不足,且大部分已有研究无法提供个性化程度较高的交互体验.针对这些问题,该研究基于学习风格模型提出了一种自适应式虚拟现实交互的新方法.该方法设计了适用于虚拟交互环境的学习风格判断方式,通过分析学习者的主客观数据来判断其学习风格,由此对交互环...     

Exploring the relation between learning style models and preferred multimedia types

There are many adaptive learning systems that adapt learning materials to student properties, preferences, and activities. This study is focused on designing such a learning system by relating combinations of different learning styles to preferred types of multimedia materials. We explore a decision model aimed at proposing learning material of an appropriate multimedia type. This study includes 272 student participants. The resulting decision model shows that students prefer well-structured learning texts with color discrimination, and that the hemispheric learning style model is the most important criterion in deciding student preferences for different multimedia learning materials. To provide a more accurate and reliable model for recommending different multimedia types more learning style models must be combined. Kolb's classification and the VAK classification allow us to learn if students prefer an active role in the learning process, and what multimedia type they prefer.     

Effects of the handheld technology instructional approach on performances of students of different achievement levels

The handheld technology selected and the ways it is implemented influences the way mathematics is taught and learnt, which in turn generates positive effects in the mathematics education. This study was conducted to examine the effects of handheld technology instructional approaches on performance of students of different achievement levels in Probability at a private higher learning institution in Malaysia. A quasi-experimental study with non-equivalent control group design with pre-test and post-test design was conducted on a sample of 65 students. The sample was divided into the experimental group and control group. The handheld technology instructional approaches, i.e. teaching and learning approaches using the graphing calculator (GC) as a teaching and learning tool and the GC instructional worksheets, were employed in the teaching and learning of probability in the experimental group. The conventional teaching approach was adopted in the control group. Quantitative and qualitative methods were employed to collect and analyse data. Quantitative data was collected using the Probability Achievement Test (PAT). PAT was administered to both groups at the beginning and end of the study. Qualitative data was collected using students' journals. The results show that students, the high, average and low achievers, gained benefits when the handheld technology instructional approaches were used in learning Probability, particularly random variable, poisson distribution, binomial distribution and normal distribution.     

Educational interface agents as social models to influence learner achievement,attitude and retention of learning

This study examined the impacts of educational interface agents with different attributes on achievement, attitude and retention of elementary school students in their science and technology courses. The study was implemented in four different eighth- grade classes (aged 13–14) of an elementary school. Four different types of educational software, covering living things and life unit of 8th graders, were developed to analyze the impacts of educational software agents with different attributes on the results of learning. The study was conducted according to experimental model with pretest and posttest control group, which is one of the quasi-experimental designs. For five consecutive weeks experimental and control group students used the software designed for this research. The students were asked to fill an attitude scale on science and technology both before and after the implementation. And following completion, an achievement test was applied. The results of the study revealed that students who used a human-like educational interface agent were more successful than both the rest of the experimental groups and the control group in terms of achievement, attitude and retention of learning in science and technology classes. It is also revealed that the software to be developed for elementary school 8th graders (aged 13–14) should be supported with human-like educational interface agents.     

The influence of learner-generated domain representations on learning combinatorics and probability theory

The aim of the current study was to examine the effects of providing support in the form of tools for constructing representations, and in particular the differential effects of the representational format of these tools (conceptual, arithmetical, or textual) in terms of perceived affordances and learning outcomes. The domain involved was combinatorics and probability theory. A between-subjects pre-test–post-test design was applied with secondary education students randomly distributed over four conditions. Participants completed the same tasks in a simulation-based learning environment. Participants in three experimental conditions were provided with a representational tool that could be used to construct a domain representation. The experimental manipulation concerned the format of the tool (conceptual, arithmetical, or textual). Participants in a control condition did not have access to a representational tool. Data from 127 students were analyzed. It was found that the construction of a domain representation significantly improved learning outcomes. The format in which students constructed a representation did not directly affect learning outcomes or the quality of the created domain representations. The arithmetical format, however, was the least stimulating for students to engage in externalizing their knowledge.     

Regulative support for collaborative scientific inquiry learning

Abstract This study examined whether online tool support for regulation promotes student learning during collaborative inquiry in a computer simulation‐based learning environment. Sixty‐one students worked in small groups to conduct a scientific inquiry with fluid dynamics. Groups in the experimental condition received a support tool with regulatory guidelines; control groups were given a version of this tool from which these instructions were removed. Results showed facilitative effects for the fully specified support tool on learning outcomes and initial planning. Qualitative data elucidated how regulative guidelines enhanced learning and suggests ways to further improve regulative processes within collaborative inquiry learning settings.