The role of feedback and self-efficacy on web-based learning: The social cognitive perspective

The social cognitive perspective of self-regulated learning suggests that effective learning is determined by the interactions among personal, behavioral, and environmental influences; particularly, high self-regulated learners hold higher motivation (personal), apply better learning strategies (behavioral) and respond to environmental demand more appropriately (environmental). The study thus uses the social cognitive perspective to explore the role of self-efficacy (personal), student feedback behavior, use of learning strategies (behavioral), performance and receiving feedback (environmental) in Web-based learning. There were 76 university students participated in this study. Both quantitative and qualitative methods were applied for data analysis. The results supported that self-efficacy predicted student use of learning strategies and related to elaborated feedback behavior (personal → behavioral). High self-efficacy students applied more high-level learning strategies, such as elaborative strategy and critical thinking. Students who provided elaborated feedback also had higher self-efficacy than those who did not. Moreover, receiving elaborative feedback significantly promoted student self-efficacy (environmental → personal), while receiving knowledge of correct response improved student performance. However, the results indicated that feedback behaviors did not predict academic performance, which may be interfered by modeling effects.     

Development of an adaptive learning system with two sources of personalization information

Previous research of adaptive learning mainly focused on improving student learning achievements based only on single-source of personalization information, such as learning style, cognitive style or learning achievement. In this paper, an innovative adaptive learning approach is proposed by basing upon two main sources of personalization information, that is, learning behavior and personal learning style. To determine the initial learning styles of the students, the [Keefe, J. W. (1987). Learning Styles: Theory and Practice. Reston, VA: National Association of Secondary School Principals.] questionnaire is employed in our approach. To more precisely reflect the learning behaviors of each student, the interactions and learning results of each student are analyzed when adjusting the subject materials. Based on the innovative approach, an adaptive learning system has been developed; moreover, an experiment was conducted to evaluate the performance of our approach. By analyzing the results from three groups of students using different adaptive learning approaches, it can be found that the innovative approach is helpful in improving both the learning achievement and learning efficiency of individual students.     

Supervised machine learning in multimodal learning analytics for estimating success in project‐based learning

Multimodal learning analytics provides researchers new tools and techniques to capture different types of data from complex learning activities in dynamic learning environments. This paper investigates the use of diverse sensors, including computer vision, user‐generated content, and data from the learning objects (physical computing components), to record high‐fidelity synchronised multimodal recordings of small groups of learners interacting. We processed and extracted different aspects of the students' interactions to answer the following question: Which features of student group work are good predictors of team success in open‐ended tasks with physical computing? To answer this question, we have explored different supervised machine learning approaches (traditional and deep learning techniques) to analyse the data coming from multiple sources. The results illustrate that state‐of‐the‐art computational techniques can be used to generate insights into the "black box" of learning in students' project‐based activities. The features identified from the analysis show that distance between learners' hands and faces is a strong predictor of students' artefact quality, which can indicate the value of student collaboration. Our research shows that new and promising approaches such as neural networks, and more traditional regression approaches can both be used to classify multimodal learning analytics data, and both have advantages and disadvantages depending on the research questions and contexts being investigated. The work presented here is a significant contribution towards developing techniques to automatically identify the key aspects of students success in project‐based learning environments, and to ultimately help teachers provide appropriate and timely support to students in these fundamental aspects.     

When educational agents meet surrogate competition: Impacts of competitive educational agents on students' motivation and performance

The design of educational agents increasingly attracts researchers' attention recently. One of major reasons is that educational agents could enhance student learning in various aspects. Although research in this area has mushroomed, such research mainly emphasizes on students in higher education. It is still unclear how educational agents influence young student learning. In addition, competition is a significant element, but fewer studies take competition into account while designing educational agents. Although some studies have indicated that educational agents in competitive environments has positive effects on students' perception and attribution, its impacts on students' motivation and performance are unclear. Thus, the study develops an integrative agent that combines educational and competitive elements for young students, and further examines its influences, in terms of motivation and learning performance. The results revealed that such competitive educational agents could enhance students' motivation and learning performance.     

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.     

Exploring quadrilaterals in a small group computing environment

Though cooperative learning has been a topic of considerable interest in educational research, there has been little study specific to learning in the mathematics content area of geometry. This paper seeks to address that gap through a design experiment featuring a novel small-group computing environment for supporting student learning about quadrilaterals. In this design, each student controls a unique point in a shared geometric space, and those points are linked such that a group of four students collectively forms a quadrilateral. We first present results from pre- and post-measures to show how the students learned from the activities and developed in terms of geometric reasoning. We then present three episodes, elaborated with the notion of appropriation, to explain how students took up ways of using the technological tools and of talking about geometric concepts from one another in the interactive environment. Our study found that students achieved learning gains in this novel environment, that the environment provided rich opportunities for peer interaction around geometric objects, and that student learning opportunities and interactions were characterized by processes of appropriating ways of talking about and using software features.     

Technology uses and student achievement: A longitudinal study

Based on data collected from a middle school, this study investigates how the quantity and quality of technology use affect student learning outcomes. Specifically, this study examines how technologies are used by students, what technology uses are popular among students, and what technology uses are effective for increasing student academic achievement. Results suggest that the quantity of technology use alone is not critical to student learning. “How much” matters when “how” is identified. Moreover, when the quality of technology use is not ensured, more time on computers may cause more harm than benefit. With students’ change in GPA as an indicator, technology uses that had positive impact on students were those related to specific subject areas and focused on student construction. In addition, analysis of the frequency of technology uses found that, in general, technology uses that had positive impact were not popular; on the contrary, some of these technology uses were the least frequently used. Implications for practice and future research are discussed in this paper.     

Facilitating application of language skills in authentic environments with a mobile learning system

We uncovered two critical issues in earlier studies: (a) some studies have shown that mobile learning technology is not beneficial for all students due to complexity of learning environments and student prior knowledge, skills, and experience and (b) familiarity of students with the authentic environments in which they learn using mobile technology did not receive much attention in earlier studies. To address these issues, we designed three learning tasks for a class of 26 junior high school students. The students applied language skills by completing the tasks in authentic environments individually in a first task, loosely collaborating with peers in a second task, and tightly collaborating with peers in a third task. A mobile learning system was also designed in this study to support students to accomplish the tasks. The aim of this study was to explore students' learning experiences using the learning system, their perceptions towards the system, and to assess how differently the students perform on the three tasks. According to our design, in the first task, the students took pictures of objects and described them orally or in writing using the mobile learning system. In the second task, after the students completed assignments, each student received comments from a partner through the system. In comments, the partner indicated flaws in student assignments and suggested how to fix them. In the third task, the students completed assignments, shared them using the system, and then exchanged comments with their partners face to face regarding issues related to their completed assignments and suggested how to improve them. Such learning behaviours in the three tasks enabled the students to practise writing and speaking skills. Our results demonstrate that most of the students highly valued our learning system and intend to use it in the future. Furthermore, the results show that the students performed best when they collaborated; namely, student performance was enhanced the most after the third task that required tight collaboration. Based on our results, we learned that students' familiarity with authentic environments is very important and beneficial for their learning. In addition, we learned that even in complex environment, less skilled and experienced students with low prior knowledge can perform well when they tightly collaborate with more skilled and experienced students with high prior knowledge, and our learning system can facilitate such collaboration.     

Adaptive product tracking in RFID-enabled large-scale supply chain

The Radio Frequency Identification (RFID) technology is gradually being adopted and deployed for product flow management in the supply chain. In order to track RFID-tagged products efficiently in the RFID-enabled, large-scale supply chain, this paper first presents the design of a product tracking system that can collaborate with the EPC Network, a suite of network services for RFID data management in the supply chain. Next, we explain a product monitoring procedure that is performed by comparing the actual path of a product with its planned path. Finally, we develop an adaptive product search algorithm based on a reinforcement learning technique to efficiently locate a product deviated from its planned path. Experiment results are provided to show the performance of the search algorithm.     

Engaging online learners: The impact of Web-based learning technology on college student engagement

Widespread use of the Web and other Internet technologies in postsecondary education has exploded in the last 15 years. Using a set of items developed by the National Survey of Student Engagement (NSSE), the researchers utilized the hierarchical linear model (HLM) and multiple regressions to investigate the impact of Web-based learning technology on student engagement and self-reported learning outcomes in face-to-face and online learning environments. The results show a general positive relationship between the use the learning technology and student engagement and learning outcomes. We also discuss the possible impact on minority and part-time students as they are more likely to enroll in online courses.     

How to improve the peer review method: Free-selection vs assigned-pair protocol evaluated in a computer networking course

This study provides field research evidence on the efficiency of a “free-selection” peer review assignment protocol as compared to the typically implemented “assigned-pair” protocol. The study employed 54 sophomore students who were randomly assigned into three groups: Assigned-Pair (AP) (the teacher assigns student works for review to student pairs), Free-Selection (FS) (students are allowed to freely explore and select peer work for review), and No Review (NR) (control group). AP and FS student groups studied and reviewed peer work in the domain of Computer Networking, supported by a web-based environment designed to facilitate the two peer review protocols. Our results indicate that students following the Free Selection protocol demonstrate (a) better domain learning outcomes, and (b) better reviewer skills, compared to the AP condition. Overall, the study analyzes the benefits and shortcomings of the FS vs AP review assignment protocol, providing evidence that the FS condition can be multiply beneficial to students who engage in peer review activities.     

Cousins Virtual Jane and Virtual Joe,extraordinary virtual helpers

Higher education institutions deliver web-based learning with varied success. The success rate of distributed online courses remains low. Factors such as ineffective course facilitation and insufficient communication contribute to the unfulfilled promises of web-based learning. Students consequently feel unmotivated. Instructor control and in the courseroom further isolates students, whereas success rate increases when students unite in virtual communities. King (2002) increased student participation in his online classes by creating a virtual student, Joe, as a participating student and supplementary facilitator. This investigation responds to King’s call for further directions on how a virtual helper enhances online facilitation. This inspired our investigation of how Virtual Jane might augment online facilitation. King’s prediction, “It seems that Joe Bags may have a family in the future,” (p. 164) became a reality in a South African masters’ web-based class on web-based learning.     

Enhancement of student learning performance using personalized diagnosis and remedial learning system

Although conventional student assessments are extremely convenient for calculating student scores, they do not conceptualize how students organize their knowledge. Therefore, teachers and students rarely understand how to improve their future learning progress. The limitations of conventional testing methods indicate the importance of accurately assessing and representing student knowledge structures. The personalized diagnosis and remedial learning system (PDRLS) proposed in this study enhances the effectiveness of the Pathfinder network by providing remedial learning paths for individual learners based on their knowledge structure. The sample was 145 students enrolled in introductory JAVA programming language courses at a Central Taiwan technology university. The experimental results demonstrate that learners who received personalized remedial learning guidance via PDRLS achieved improved learning performance, self-efficacy, and PDRLS use intention. The experimental results also indicated that students with lower knowledge level gain more benefits from the PDRLS than those with higher level of knowledge and that field dependence (FD) students obtain a greater benefit from PDRLS than field independence (FI) students do.     

How science students can learn about unobservable phenomena using computer-based analogies

A novel instructional computer simulation that incorporates a dynamic analogy to represent Le Chatelier’s Principle was designed to investigate the contribution of this feature to students’ understanding. Two groups of 12th grade Chemistry students (n = 15) interacted with the computer simulation during the study. Both groups did the same pre-instructional and simulation activities except one of the groups interacted with the analogical example in the simulation and the other group was asked to recall an analogy that was presented in the form of text and pictures. A statistical analysis of the tests administered at the end of the study suggested that analogies that are dynamic, interactive, and integrated in a computer simulation may have a stronger effect on learning outcomes than analogies which are presented in the form of text and static pictures. The implication of this study for science educators is that dynamic computer-based analogies can enhance student learning of unobservable phenomena in science.     

The role of student learning styles, gender, attitudes and perceptions on information and communication technology assisted learning

The present study adopts an illuminative approach to evaluate students’ initial attitudes towards the use of information and communication technology (ICT). Ninety-nine undergraduate science students participated in this study and their learning styles were classified according to Honey and Mumford (1986) (Honey, P., Mumford, A., 1986. The Manual of Learning styles. Peter Honey, 10 Linden Avenue, Maidenhead) learning style questionnaire. Student learning styles were classified as activist, reflector, theorist, or pragmatist. No significant difference in learning styles was observed between genders and between student cohorts. Six dimensions to student attitudes toward ICT were identified as follows; ‘comfort’, ‘interactivity’, ‘self-satisfaction’, ‘value new technology’, ‘experience’ and ‘context’. Students exhibited low scores in the attitude dimensions of ‘value new technology’, ‘interactivity’ and ‘context’ indicating that they were uncomfortable with computers, were unhappy about the lack of personal contact and would prefer to learn in a more traditional mode. A significant, though weak, negative correlation between the ‘theorist’ and the ‘interactivity’ and ‘context’ attitude dimensions was also observed. In addition, based on the results of this study it appears that first year students exhibit a more positive perception of ICT supported learning than second and third year students. Though the use of ICT in higher education is becoming more widespread based on the results of this study student use of the technology may be limited by a negative attitude toward a style of teaching which is not consistent with their past learning experiences.     

Engagement and performance in a first year natural resource science course

Quantifying student engagement with online learning resources on virtual learning environments such as BlackBoard is important in understanding how these technologies enhance the student learning. In the present study, it was examined when, and how often, first‐year students accessed lecture recordings, lecture slides, and lecture notes via BlackBoard, in an introductory natural resource course taken by both on campus students and remote students. The findings demonstrated that lecture recordings were not well utilized by students—although only 58% of on campus students attended face‐to‐face lectures, less than 15% of absent students downloaded the missed lecture. Overall, more students downloaded lecture slides (an average of 63% per week) than notes (38%) or recordings (16%). Indeed, the average student downloaded only 1.1 types of the 3 online resources (recordings, slides, and notes) that were available each week, with 5.7% of students downloading all 3 types of resources, 23% downloading 2 types of resources, 42% downloading only 1 type of resource, and 29% downloading none of the 3 types of resources. Finally, remote students were more likely to download lecture notes and recordings than were on campus students. The information presented here is important in understanding student behaviour and engagement.     

eTeacher: Providing personalized assistance to e-learning students

In this paper we present eTeacher, an intelligent agent that provides personalized assistance to e-learning students. eTeacher observes a student’s behavior while he/she is taking online courses and automatically builds the student’s profile. This profile comprises the student’s learning style and information about the student’s performance, such as exercises done, topics studied, exam results. In our approach, a student’s learning style is automatically detected from the student’s actions in an e-learning system using Bayesian networks. Then, eTeacher uses the information contained in the student profile to proactively assist the student by suggesting him/her personalized courses of action that will help him/her during the learning process. eTeacher has been evaluated when assisting System Engineering students and the results obtained thus far are promising.     

Computer support for learning mathematics: A learning environment based on recreational learning objects

In this paper, we introduce an electronic collaborative learning environment based on Interactive Instructors of Recreational Mathematics (IIRM), establishing an alternative approach for motivating students towards mathematics. The IIRM are educational software components, specializing in mathematical concepts, presented through recreational mathematics, conceived as interactive, recreation-oriented learning objects, integrated within the environment. We present the architecture of the learning environment which integrates communication services that support the interaction processes of the learning community, through instant messaging, chat rooms, and multi-player math games. Through the environment’s interface of their personal workspace, students have access to several easy-to-use mechanisms that allows them to customize its content, its layout, and its appearance. At internal levels, the functionality of IIRM is enhanced with features supported by the environment infrastructure. We evaluated different aspects of the learning environment in three short, motivation-oriented math courses given to Mexican high-school students. The results indicate that the use of the IIRM-based electronic learning environment, positively affects student attitudes towards mathematics. We believe that this approach has the potential to promote the mathematics learning process, basically on its motivational aspects.     

Tool-use in a blended undergraduate course: In Search of user profiles

The popularity of today’s blended courses in higher education is driven by the assumption that students are provided with a rich toolset that supports them in their learning process. However, little is known on how students actually use these tools and how this affects their performance for the course. The current study investigates how students use the entire toolset at their disposal, whether tool-use patterns can be found and if these patterns affect performance for the course. Logging students (n = 156) actions throughout the content management system and registering students’ use of the face-to-face support in an undergraduate course, the study reveals large student differences and an underuse for some tool-types. Further to this, K-means cluster analysis reveals three distinct tool-use patterns or user profiles: the no-users, the intensive users and the incoherent users. These patterns are characterized by different tool-choices and even different use intensity among students. Evidence is retrieved that these tool-use differences are problematic since multivariate analysis of variance reveals significant performance effects. Hence, these results imply that not all students seem to profit from the learning affordances that are provided. Similar as evidence in controlled settings, the results suggest that learner control in using tools cannot be taken for granted. Consequently, this study legitimates more research into the influencing (student and context) variables that can explain these differences.