Applying learning analytics dashboards based on process-oriented feedback to improve students' learning effectiveness

With the development of a technology-supported environment, it is plausible to provide rich process-oriented feedback in a timely manner. In this paper, we developed a learning analytics dashboard (LAD) based on process-oriented feedback in iTutor to offer learners their final scores, sub-scale reports, and corresponding suggestions on further learning content. We adopted a quasi-experimental design to investigate the effectiveness of the report on students' learning. Ninety-four freshman from two classes participated in this research. The two classes were divided into the LAD group and the original analytics report (OAR) based on a product-oriented feedback group. Before the experiment, all the students took the prior knowledge assessment. After a semester's instruction, all the students took the post-test of the summative assessment. Results indicated that students in the LAD group experienced better learning effectiveness than students in the OAR group. LAD based on process-oriented feedback was also effective in improving the skill learning effectiveness of the students with low-level prior knowledge.     

Learning with intelligent tutors and worked examples: selecting learning activities adaptively leads to better learning outcomes than a fixed curriculum

The main learning activity provided by intelligent tutoring systems is problem solving, although several recent projects investigated the effectiveness of combining problem solving with worked examples. Previous research has shown that learning from examples is an effective learning strategy, especially for novice learners. A worked example provides step-by-step explanations of how a problem is solved. Many studies have compared learning from examples to unsupported problem solving, and suggested presenting worked examples to students in the initial stages of learning, followed by problem solving once students have acquired enough knowledge. This paper presents a study in which we compare a fixed sequence of alternating worked examples and tutored problem solving with a strategy that adapts learning tasks to students’ needs. The adaptive strategy determines the type of the task (a worked example, a faded example or a problem to be solved) based on how much assistance the student received on the previous problem. The results show that students in the adaptive condition learnt significantly more than their peers who were presented with a fixed sequence of worked examples and problem solving. Novices from the adaptive condition learnt faster than novices from the control group, while the advanced students from the adaptive condition learnt more than their peers from the control group.     

Building virtual cities,inspiring intelligent citizens: Digital games for developing students’ problem solving and learning motivation

This study investigates the effectiveness digital game-based learning (DGBL) on students’ problem solving, learning motivation, and academic achievement. In order to provide substantive empirical evidence, a quasi-experimental design was implemented over the course of a full semester (23 weeks). Two ninth-grade Civics and Society classes, with a total of 44 students (15–16 years old), were randomly assigned to one of two conditions: an experimental group (incorporating DGBL) and a comparison group (taught using traditional instruction). Two-way mixed ANOVA was employed to evaluate changes in problem solving ability and compare the effectiveness the two strategies, while ANCOVA was used to analyze the effects on learning motivation and academic achievement. The results of this study are summarized as follows: (1) The DGBL strategy was clearly effective in promoting students’ problem solving skills, while the control group showed no improvement. Additionally, data from the mid-test and post-test demonstrate that, as a higher order thinking skill, problem-solving requires a full semester to develop. (2). DGBL resulted in better learning motivation for students in the experimental group as compared to learners receiving TI. (3) Contrary to some suggestions that digital games could inhibit academic achievement, no statistically significant difference was found between the two groups. Most importantly, the quantitative improvement in problem-solving and learning motivation suggest that DGBL can be exploited as a useful and productive tool to support students in effective learning while enhancing the classroom atmosphere. Future research in DGBL should emphasize the evaluation of other higher order elements of the cognitive domain in terms of academic achievement outcomes and skills, such as critical and creative thinking.     

An analysis of students�� gaming behaviors in an intelligent tutoring system: predictors and impacts

Students who exploit properties of an instructional system to make progress while avoiding learning are said to be ??gaming?? the system. In order to investigate what causes gaming and how it impacts students, we analyzed log data from two Intelligent Tutoring Systems (ITS). The primary analyses focused on six college physics classes using the Andes ITS for homework and test preparation, starting with the research question: What is a better predictor of gaming, problem or student? To address this question, we developed a computational gaming detector for automatically labeling the Andes data, and applied several data mining techniques, including machine learning of Bayesian network parameters. Contrary to some prior findings, the analyses indicated that student was a better predictor of gaming than problem. This result was surprising, so we tested and confirmed it with log data from a second ITS (the Algebra Cognitive Tutor) and population (high school students). Given that student was more predictive of gaming than problem, subsequent analyses focused on how students gamed and in turn benefited (or not) from instructional features of the environment, as well as how gaming in general influenced problem solving and learning outcomes.     

A flowchart‐based intelligent tutoring system for improving problem‐solving skills of novice programmers

Intelligent tutoring and personalization are considered as the two most important factors in the research of learning systems and environments. An effective tool that can be used to improve problem‐solving ability is an Intelligent Tutoring System which is capable of mimicking a human tutor's actions in implementing a one‐to‐one personalized and adaptive teaching. In this paper, a novel Flowchart‐based Intelligent Tutoring System (FITS) is proposed benefiting from Bayesian networks for the process of decision making so as to aid students in problem‐solving activities and learning computer programming. FITS not only takes full advantage of Bayesian networks, but also benefits from a multi‐agent system using an automatic text‐to‐flowchart conversion approach for engaging novice programmers in flowchart development with the aim of improving their problem‐solving skills. In the end, in order to investigate the efficacy of FITS in problem‐solving ability acquisition, a quasi‐experimental design was adopted by this research. According to the results, students in the FITS group experienced better improvement in their problem‐solving abilities than those in the control group. Moreover, with regard to the improvement of a user's problem‐solving ability, FITS has shown to be considerably effective for students with different levels of prior knowledge, especially for those with a lower level of prior knowledge.     

Lifelike Pedagogical Agents for Mixed-initiative Problem Solving in Constructivist Learning Environments

Mixed-initiative problem solving lies at the heart of knowledge- based learning environments. While learners are actively engaged in problem-solving activities, learning environments should monitor their progress and provide them with feedback in a manner that contributes to achieving the twin goals of learning effectiveness and learning efficiency. Mixed-initiative interactions are particularly critical for constructivist learning environments in which learners participate in active problem solving. We have recently begun to see the emergence of believable agents with lifelike qualities. Featured prominently in constructivist learning environments, lifelike pedagogical agents could couple key feedback functionalities with a strong visual presence by observing learners' progress and providing them with visually contextualized advice during mixed-initiative problem solving. For the past three years, we have been engaged in a large-scale research program on lifelike pedagogical agents and their role in constructivist learning environments. In the resulting computational framework, lifelike pedagogical agents are specified by(1) a behavior space containing animated and vocal behaviors,(2) a design-centered context model that maintains constructivist problem representations, multimodal advisory contexts, and evolving problem-solving tasks, and(3) a behavior sequencing engine that in realtime dynamically selects and assembles agents' actions to create pedagogically effective, lifelike behaviors.To empirically investigate this framework, it has been instantiated in a full-scale implementation of a lifelike pedagogical agent for Design-A-Plant, a learning environment developed for the domain of botanical anatomy and physiology for middle school students. Experience with focus group studies conducted with middle school students interacting with the implemented agent suggests that lifelike pedagogical agents hold much promise for mixed-initiative learning.     

Improving mathematical problem solving: A computerized approach

Mathematics teachers often experience difficulties in teaching students to become skilled problem solvers. This paper evaluates the effectiveness of two interactive computer programs for high school mathematics problem solving. Both programs present students with problems accompanied by instruction on domain-specific knowledge required in different episodes of problem solving. The first program is based on a direct instructional approach to learning, the second on a constructivist view of learning. The latter approach is expected to be particularly beneficial to weak students.The effectiveness of both computer programs was evaluated by means of an experiment. Four classes worked with the constructivist based computer program, and four worked with the direct instructional program. Five classes that had received traditional mathematics education served as the control group. The computer programs were used in three periods of two consecutive weeks each. The results show that both computer programs improved problem-solving ability more strongly than had traditional mathematics instruction. Contrary to our expectations, both weak and skilled students benefited equally from both computer programs. Specifically, the programs helped the students to improve the quality of their analysis and verification skills during problem solving.     

Problem solving and collaboration using mobile serious games

This paper presents the results obtained with the implementation of a series of learning activities based on Mobile Serious Games (MSGs) for the development of problem solving and collaborative skills in Chilean 8th grade students. Three MSGs were developed and played by teams of four students in order to solve problems collaboratively. A quasi-experimental design was used. The data shows that the experimental group achieved a higher perception of their own collaboration skills and a higher score in the plan execution dimension of the problem solving cycle than did the non-equivalent control group, revealing that MSG-based learning activities may contribute to such learning improvements. This challenges future research to identify under which conditions learning activities based on mobile serious games can promote the development of higher order skills.     

Problem solving, planning ability and sharing processes with LOGO

The present research examined the impact of a Logo environment on the level of problem solving control, modification of planning ability and sharing processes in pairs and individual learners. Forty-five fifth-grade students (ranging in age from 10 to 11 years old, who studied in four classes), participated in the study. The subjects were randomly divided into fifteen pairs and fifteen individuals. Results showed significant differences in problem solving control between the Logo environment group and the comparison group. At the end of the treatment the degree of cooperative learning increased in the pairs groups. There was an effective modification of the subjects' planning ability in both pairs and individuals.     

An analysis of collaborative problem‐solving activities mediated by individual‐based and collaborative computer simulations

Researchers have indicated that the collaborative problem‐solving space afforded by the collaborative systems significantly impact the problem‐solving process. However, recent investigations into collaborative simulations, which allow a group of students to jointly manipulate a problem in a shared problem space, have yielded divergent results regarding their effects on collaborative learning. Hence, this study analysed how students solved a physics problem using individual‐based and collaborative simulations to understand their effects on science learning. Multiple data sources including group discourse, problem‐solving activities, learning test scores, and questionnaire feedback were analysed. Lag sequential analysis on the data found that students using the two simulations collaborated with peers to solve the problem in significantly different patterns. The students using the collaborative simulations demonstrated active engagement in the collaborative activity; however, they did not transform discussions into workable problem‐solving activities. The students using the individual‐based simulation showed a lower level of collaboration engagement, starting with individual exploration of the problem with the simulation, followed by group reflection. The two groups also showed significant differences in their learning test scores. The findings and pedagogical suggestions are discussed in the hope of addressing critical activity design issues in using computer simulations for facilitating collaborative learning.     

Relationship between perceived problem‐solving skills and academic performance of novice learners in introductory programming courses

Past research has shown that student problem‐solving skills may be used to determine student final exam performance. This study reports on the relationship between student perceived problem‐solving skills 1 1 Henceforth, for brevity, we drop the word “perceived” in “student perceived problem‐solving skills” and use either “student perceived problem solving” or simply “student PSS.”
and academic performance in introductory programming, in formative and summative programming assessment tasks. We found that the more effective problem solvers achieved better final exam scores. There was no significant difference in formative assessment performances between effective and poor problem solvers. It is also possible to categorize students on the basis of problem‐solving skills, in order to exploit opportunities to improve learning around constructivist learning theory. Finally, our study identified transferability skills and the study may be extended to identify the impact of problem solving transfer skills on student problem solving for programming.     

Analysis of peer learning behaviors using multiple representations in virtual reality and their impacts on geometry problem solving

Learning geometry emphasizes the importance of exploring different representations such as virtual manipulatives, written math formulas, and verbal explanations, which help students build math concepts and develop critical thinking. Besides helping individuals construct math knowledge, peer interaction also plays a crucial role in promoting an understanding of mathematics and geometric problem solving. In this research, an Interactive Future Mathematics Classroom (IFMC) based on the Collaborative Virtual Reality Learning Environment (CVRLE) was proposed to facilitate three-dimensional (3-D) geometric problem solving. Two representational tools, the virtual manipulative and a white board, were integrated into the IFMC to help students with the following activities: to synchronously review peers' solving processes; to individually or collaboratively manipulate 3-D objects using the virtual manipulative; and to give comments on peers' white boards for future queries and discussions. One eight-week experiment was conducted and the results showed that the experimental group using the IFMC performed significantly better than the control group on geometric learning achievement. Further analysis showed that the peer learning behaviors of the experimental group in the two kinds of geometric problems, volume and surface area calculation, were different due to the problems' varying difficulty levels. Moreover, various peer learning behaviors with multiple representations lead to different types of strategies for geometric problem solving in the IFMC. Therefore, peer learning behaviors in the IFMC were found useful to facilitate geometric problem solving by sharing ideas and exploring multiple representations.     

A conceptual framework mapping the application of information search strategies to well and ill-structured problem solving

Problem-based learning (PBL) is an instructional approach that is organized around the investigation and resolution of problems. Problems are neither uniform nor similar. 11 and 12 in his design theory of problem solving has categorized problems into two broad types – well-structured and ill-structured. He has also described a host of mediating skills that impact problem solving outcomes. The thrust of this paper rests in the argument that the basis of these mediating skills is information search literacy and particularly, in view of the utility of the Internet as an informational repository, effective information searching skills. This study was an investigation of how different Internet information seeking strategies can be used to engage in problem solving. A conceptual framework that explains how different Internet information searching strategies can be employed in successfully solving well and ill-structured problems was devised and empirically tested. The research site was a newly established polytechnic in Singapore that employs problem-based learning to support its curricular implementation. The sample population of students came from a class of 25 first-year students. The research findings of this study inform that information searching skills indeed play an important role in problem solving. The findings affirm the need for students to be systematically instructed in the skills of information searching to be able to accomplish problem solving. The information searching necessary for solving well-structured problems is constrained and readily manageable. Thus, students only have to be acquainted with fundamental information searching skills to solve well-structured problems. On the other hand, the information needs of ill-structured problems are usually complex, multi-disciplinary and expansive. Hence, students have to be trained to apply a more advanced set of information searching skills in resolving ill-structured problems.     

The impact of goal specificity and goal type on learning outcome and cognitive load

Two hundred and thirty three 15-year old students conducted experiments within a computer-based learning environment. They were provided with different goals according to an experimental 2 × 2 design with goal specificity (nonspecific goals versus specific goals) and goal type (problem solving goals versus learning goals) as factors. We replicated the findings of other researchers that nonspecific problem solving goals lead to lower cognitive load and better learning than specific problem solving goals. For learning goals, however, we observed this goal specificity effect only on cognitive load but not on learning outcome. Results indicate that the goal specificity affects the element interactivity of a task and cognitive load with both, problem solving goals or learning goals. But differences in overall cognitive load are not sufficient for explaining differences in learning outcome. Additionally, differences in strategy use come into play. Specific problem solving goals seem to restrict students to use a problem solving strategy whereas nonspecific problem solving goals or learning goals allow students to use a learning strategy. We conclude that in order to foster learning, students must be provided with goals that allow them to use a learning strategy. Additionally, providing them with nonspecific goals decreases cognitive load and, thus, enables students to learn with less effort.     

Effects of mental process integrated nursing training using mobile device on students’ cognitive load,learning attitudes,acceptance, and achievements

Clinical nursing training is important to nursing educators and student nurses in nursing education since safe and competent care depends on good clinical problem solving skills. Therefore, developing better cognitive problem-solving strategies or tools are essential for clinical nursing practices. Moreover, learning diagnosis is also a critical determinant in the acquisition, processing, and application of clinical skills in nursing practices. Bearing this in mind, this study aims to develop a mobile interactive learning and diagnosis (MILD) system to support problem-based learning (PBL) in a clinical nursing course based on the testing-based approach. Using mobile devices as a learning tool to integrate both real-world and digital-world resources for students and adopting PBL as a learning strategy to facilitate the development of the clinical problem solving skills. To show the effectiveness of the proposed approach, an experiment was conducted in a foundations of nursing course at a nursing college in Taiwan. The experimental results show that the proposed approach is helpful to students in improving learning performance and reducing cognitive loads. Moreover, it was also found that most students showed positive perceptions toward the usage of the proposed system.     

Completion strategy or emphasis manipulation? Task support for teaching information problem solving

While most students seem to solve information problems effortlessly, research shows that the cognitive skills for effective information problem solving are often underdeveloped. Students manage to find information and formulate solutions, but the quality of their process and product is questionable. It is therefore important to develop instruction for fostering these skills. In this research, a 2-h online intervention was presented to first-year university students with the goal to improve their information problem solving skills while investigating effects of different types of built-in task support. A training design containing completion tasks was compared to a design using emphasis manipulation. A third variant of the training combined both approaches. In two experiments, these conditions were compared to a control condition receiving conventional tasks without built-in task support. Results of both experiments show that students' information problem solving skills are underdeveloped, which underlines the necessity for formal training. While the intervention improved students’ skills, no differences were found between conditions. The authors hypothesize that the effective presentation of supportive information in the form of a modeling example at the start of the training caused a strong learning effect, which masked effects of task support. Limitations and directions for future research are presented.     

分段学习的双隐层BPNN对交通流量预测的研究

智能交通系统可有效解决城市道路的拥挤,交通流量的预测是智能交通系统的关键技术之一。在各种预测方法中,BP神经网络的应用最普遍,并取得了许多成果。为了进一步提高BP神经网络的预测精度,采用了基于分段学习的双隐层BP神经网络对济南市经十路的交通流量进行了预测,并与相同结构未使用分段学习方法的BP神经网络预测所得结果进行了比较。实验数据显示采用分段学习的方法比未采用该方法的所得结果平均相对误差减少了2.52%。因此分段学习的双隐层BP神经网络可应用于预测道路交通流量。     

Perceptions of learning effectiveness in M‐learning: scale development and student awareness

The purpose of this study is to develop a multi‐dimensional scale to measure students' awareness of key competencies for M‐learning and to test its reliability and validity. The Key Competencies of Mobile Learning Scale (KCMLS) was determined via confirmatory factor analysis to have four dimensions: team collaboration, creative thinking, critical thinking and problem solving, and communication. The research subjects are 815 students from the elementary school that participate in M‐learning programme in Taiwan. The research results show that students have better self‐awareness in team collaboration and creative thinking, but have worse self‐awareness in critical thinking and problem solving. This study also found that there was no significant difference between genders in the KCMLS, but students who study in the schools that committed in M‐learning longer have higher awareness in all dimensions than students who study in the schools that committed to M‐learning in fewer years.     

An investigation into effectiveness of different reflective learning strategies for learning operational software

Skill certification promotion is one of the main policies facilitated by the technological and vocational education, where application software instruction is regarded as the core curriculum to foster skill certification. With its close connection with problem-solving learning, application software instruction relies heavily on hands-on operation incorporating information technology to adequately unravel the challenges where living or working application is simulated as problem situations. According to Dewey (1963) and Edwards (1996), the process of reflection is characterized by the inference course where learners attempt to analyze and solve the problems. However, more evidence is needed to decide what reflective learning strategies are effective for students' learning. Application software operation is categorized as procedural knowledge. Repeated drills are requisite to reach the ultimate goal of spontaneous reaction without thinking. Features of CAL system offer a well-rounded environment to meet the demands. The purposes of this study were 1) to investigate how different reflective learning strategies can affect learning effectiveness of operational application software acquisition, 2) to identify effective learning strategies and to incorporate the CAL approach with instructional practices to foster learning performance. Aiming at characteristics of operational software, this study proposed operational software learning strategy theory model based on reflective learning and Adaptive Character of Thought-Rational (ACT-R) model theories. The proposed model modified the reflective learning theory and added cyclical loop into CAL to fit for operational software instruction. The CAL system is developed and incorporated into learning activities of reflective learning theory strategy model by collecting frequent operation errors made in the first-year experiment as the source drill items. This study is conducted in a two-year sequence. A total of 172 second-grade students was recruited from a vocational high school. Different reflective learning strategies, individual and group reflective learning strategy, are implemented on two experimental groups in the first year. CAL strategy is later added into the experimental groups in the second year. The results suggest that group reflective learning strategy can enhance learning effectiveness of the holistic and medium-score group students. When reflective learning strategy is incorporated with CAL, in addition to maintaining the first-year learning effectiveness, learning effectiveness of the holistic and low-score group students can be benefited by individual reflective learning strategy. Furthermore, reflective learning incorporating with CAL has greater learning effectiveness than the learning without CAL.     

The effects of an interactive videodisc training program in classroom observation skills used as a teaching tool and as a learning tool

In higher education, instruction is typically teacher-directed through traditional lecture formats and assignments with predetermined criteria. Through hypermedia-based materials, new ways of learning are possible based on learner control and self-directed instruction; such approaches require personal goal-setting, nonlinear exploration of materials, context-based problem solving, and progress monitoring. For students to learn in new ways, instructors have to teach in new ways. Teachers cannot simply take new hypermedia applications and implement them within existing approaches if higher level outcomes are to be realized. The findings in this study are consistent with previous research studies which demonstrate equal or better learning using hypermedia-based instructional materials when students are allowed learner control. If the learning profile for each student determines the effective use of an application, then hypermedia is best implemented as a learning tool.