Engaging first‐year students through online collaborative assessments

Substantial increases in the size of many undergraduate classes in recent years have limited the ways in which students can engage with their disciplines and become active participants in their learning. This paper presents a methodology which uses a basic WebCT platform to improve the way in which students in large classes learn. The approach, termed the Collaborative Online Assessment approach, provides a structured, scaffolded learning environment for students to engage with their peers in collaborative assessments. Results from a year‐long application of the approach with first‐year psychology students are presented. These show that the approach facilitates active student engagement throughout the academic year, and is associated with improved marks in the final written exam. This improvement in exam performance is significantly greater for students not intending to major in psychology (traditionally poorer performers). The paper discusses the implications of these findings in relation to learning theories and provides a critique for further improvement of the approach.     

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.     

Scaffolding wiki‐supported collaborative learning for small‐group projects and whole‐class collaborative knowledge building

While educators value wikis' potential, wikis may fail to support collaborative constructive learning without careful scaffolding. This article proposes literature‐based instructional methods, revised based on two expert instructors' input, presents the collected empirical evidence on the effects of these methods and proposes directions for future refinements. The instructional methods were implemented by an expert instructor teaching a 12‐week 68‐student undergraduate design class in Canada. Data were collected from observations, interviews and content analysis of wikis. The findings revealed that in small‐group project (SGP), the wiki instructional methods enhanced collaborative learning with most instructional methods derived from cooperative learning, but in whole‐class collaborative knowledge building (CKB), the wiki instructional mehtods failed to turn the class into a self‐sustained learning community after the scaffolding faded. We conclude that the genre of wikis should be different for SGP and CKB. While the students easily adopted the ‘reproduced’ genre of wikis for SGP with familiar tasks, they felt overwhelmed or resistant to the unfamiliar ‘emergent’ genre of wikis for CKB in massive collaborative constructive learning. Therefore, we propose that future refinements for wiki‐supported CKB should focus on providing students scaffolding for intersubjectivity (understanding collaborative constructive learning) and transfer of responsibility (developing autonomy).     

A web based collaborative testing environment

This paper presents a computer supported collaborative testing system built upon the Siette web-based assessment environment. The application poses the same set of questions to a group of students. Each student in the group should answer the same question twice. An initial response is given individually, without knowing the answers of others. Then the system provides some tools to show the other partners' responses, to support distance collaboration. Finally a second individual answer is requested. In this way assessment and collaboration activities are interlaced. At the end of a collaborative testing session, each student will have two scores: the initial score and the final score. Three sets of experiments have been carried out: (1) a set of experiments designed to evaluate and fine tune the application, improve usability, and to collect users' feelings and opinions about the system; (2) a second set of experiments to analyze the impact of collaboration in test results, comparing individual and group performance, and analyzing the factors that correlate to those results; and (3) a set of experiments designed to measure individual short-term learning directly related to the collaborative testing activity. We study whether the use of the system is associated with actual learning, and whether this learning is directly related to collaboration between students. Our studies confirm previous results and provide the following evidence (1) the performance increase is directly related to the access to other partners' answers; (2) a student tends to reach a common answer in most cases; and (3) the consensus is highly correlated with the correct response. Moreover, we have found evidence indicating that most of the students really do learn from collaborative testing. High-performing students improve by self-reflection, regardless the composition of the group, but low-performing students need to be in a group with higher-performing students in order to improve.     

Efficiency of learning environment using GeoGebra when calculus contents are learned in collaborative groups

In this paper we present a modern approach of teaching mathematics based on the computer supported collaborative learning (CSCL) of calculus contents. The collaborative learning was used in calculus course at the University of Novi Sad, Serbia, for examining functions and drawing their graphs. In 2012 the authors decided to improve the collaborative learning introducing GeoGebra application. Small four member groups were formed by using Kagan's (1994) principles. Two groups of students, the experimental, and the control one were observed. The students in the experimental group learned with the help of GeoGebra, and the students in the control group learned without using GeoGebra.Comparison between those two groups of the first year calculus students, regarding their way of learning and the results achieved, is described below. Before the students' collaborative learning, they were tested with a pre-test and their knowledge necessary for examining functions was verified. The pre-test showed that there was no significant statistical difference between the experimental and the control group. The experimental group worked with the help of the computer and the control one without it. After the collaborative learning, the students were tested with a test (colloquium) and the results of the experimental group were significantly better than the results of students in the control group. At the end of the course the students did their exams (post-test), and the results of the experimental group were significantly better than the results of students in the control group.Some students from the experimental group had to answer questions in an interview related to the use of GeoGebra during their collaborative learning. In order to see the students' difficulties in solving problems, students in the experimental group were asked to cross out incorrect parts of solutions, not to erase them. The teachers reviewed the students' tasks done during the collaborative learning and after that the students who had corrected their mistakes were invited for an interview about using GeoGebra for overcoming their difficulties. Based on the students' results in the tests, answers in the questionnaire and in the interview, it can be concluded that GeoGebra has enabled an easier learning of this material. The GeoGebra package enables the students to check whether each step in the process of solving a task was correctly done or not. The results of our research show that GeoGebra can help those students having insufficient knowledge (necessary for solving those tasks) to improve it.We can say that our research shows that the students' learning achievement in examining functions and drawing their graphs is better when they use GeoGebra, working in collaborative groups than without using it. Also, GeoGebra enables creation of effective learning environment for examining functions and drawing their graphs.     

Coalescing individual and collaborative learning to model user linguistic competences

A linguistic, pedagogic and technological framework for an ICALL system called COPPER is presented here, where individual and collaborative learning are combined within a constructivist approach to facilitate second language learning. Based upon the Common European Framework of Reference for Languages, the ability to use language is viewed as one of several cognitive competences that are mobilised and modified when individuals communicate. To combine the different types of learning underlying the European Framework, a student model has been developed for COPPER that represents linguistic competences in a detailed way, combining high granularity expert-centric Bayesian networks with multidimensional stereotypes, and is updated following student activities semi-automatically. Instances of this model are used by an adaptive group formation algorithm that dynamically generates communicative groups based upon the linguistic capabilities of available students, and a collection of collaborative activity templates. As well as the student model, which is a representation of individual linguistic knowledge, preferences, etc., there is a group model, which is a representation of how a set of students works together. The results of a student’s activity within a group are evaluated by a student monitor, with more advanced linguistic competences, thereby sidestepping the difficulties present when using NLP techniques to automatically analyse non-restricted linguistic production. The monitor role empowers students and further consolidates what has been previously learnt. Students therefore initially work individually in this framework on certain linguistic concepts, and subsequently participate in authentic collaborative communicative activities, where their linguistic competences can develop approximately as they would in ‘real foreign language immersion experiences’.     

Online engagement during COVID-19: Role of agency on collaborative learning orientation and learning expectations

During the COVID-19 outbreak, students had to cope with succeeding in video-conferencing classes susceptible to technical problems like choppy audio, frozen screens and poor Internet connection, leading to interrupted delivery of facial expressions and eye-contact. For these reasons, agentic engagement during video-conferencing became critical for successful learning outcomes. This study explores the mediating effect agentic engagement has on collaborative language learning orientations (CLLO) within an EFL video-conferencing course to understand better how interactions influence academic learning expectations. A total of 329 (Male = 132, Female = 197) students were recruited from four South Korean universities to participate in this questionnaire study. Data analysis was carried out using the statistical software packages SPSS, and a series of data screening procedures were carried out. Findings revealed that collaborative language learning orientations were a statistically significant predictor of academic learning expectations, but this relationship was fully mediated when agentic engagement was added to the model. Students with a propensity for social language learning strategies believe they will succeed; however, this relationship is explained by their propensity to interact with the instructor when video-conferencing. An assortment of learning activities should be provided to support both collaborative and individual learning orientations for academic success. Students with collaborative learning tendencies and a propensity to actively engage the instructor during video conference classes are active participants in the eLearning context, possibly leading to positive course expectations.     

A noise‐resilient collaborative learning approach to content‐based image retrieval

We propose to combine short‐term block‐based fuzzy support vector machine (FSVM) learning and long‐term dynamic semantic clustering (DSC) learning to bridge the semantic gap in content‐based image retrieval. The short‐term learning addresses the small sample problem by incorporating additional image blocks to enlarge the training set. Specifically, it applies the nearest neighbor mechanism to choose additional similar blocks. A fuzzy metric is computed to measure the fidelity of the actual class information of the additional blocks. The FSVM is finally applied on the enlarged training set to learn a more accurate decision boundary for classifying images. The long‐term learning addresses the large storage problem by building dynamic semantic clusters to remember the semantics learned during all query sessions. Specifically, it applies a cluster‐image weighting algorithm to find the images most semantically related to the query. It then applies a DSC technique to adaptively learn and update the semantic categories. Our extensive experimental results demonstrate that the proposed short‐term, long‐term, and collaborative learning methods outperform their peer methods when the erroneous feedback resulting from the inherent subjectivity of judging relevance, user laziness, or maliciousness is involved. The collaborative learning system achieves better retrieval precision and requires significantly less storage space than its peers. © 2011 Wiley Periodicals, Inc.     

Mine,ours, and yours: Whose engagement and prior knowledge affects individual achievement from online collaborative learning?

In computer-supported collaborative learning research, studies examining the combined effects of individual level, group level and within-group differences level measures on individual achievement are scarce. The current study addressed this by examining whether individual, group and within-group differences regarding engagement and prior knowledge predict individual achievement. Engagement was operationalised as group members' exhibited activities in the task space (i.e., discussing domain-content) and social space (i.e., regulating ideas, actions and socioemotional processes). Prior knowledge and achievement were operationalised as group members' performance on a domain-related pre-test and post-test, respectively. Data was collected for 95 triads of secondary education students collaborating on a complex business-economics problem. Subsequently, three different multilevel models were tested to examine the combined effect. First a model with the individual level measures (model 1) was tested and in subsequent models the group level measures (model 2) and within-group levels measures (model 3) were added. Findings indicate model 2 showed the best fit; group members' individual engagement in the social space activities as well as the groups' average prior knowledge positively predicts individual achievement. No effects were found for either group members' or groups' engagement in the task space and for the within-group differences.     

The concept of flow in collaborative game-based learning

Generally, high-school students have been characterized as bored and disengaged from the learning process. However, certain educational designs promote excitement and engagement. Game-based learning is assumed to be such a design. In this study, the concept of flow is used as a framework to investigate student engagement in the process of gaming and to explain effects on game performance and student learning outcome. Frequency 1550, a game about medieval Amsterdam merging digital and urban play spaces, has been examined as an exemplar of game-based learning. This 1-day game was played in teams by 216 students of three schools for secondary education in Amsterdam. Generally, these students show flow with their game activities, although they were distracted by solving problems in technology and navigation. Flow was shown to have an effect on their game performance, but not on their learning outcome. Distractive activities and being occupied with competition between teams did show an effect on the learning outcome of students: the fewer students were distracted from the game and the more they were engaged in group competition, the more students learned about the medieval history of Amsterdam. Consequences for the design of game-based learning in secondary education are discussed.     

Engaging middle school students in scientific practice with a collaborative mobile game

Previous research using collaborative mobile augmented reality games in science education revealed that such games can be used to promote learner engagement and have found that engagement in such mobile games is related to flow. This study investigated whether player's flow experience differed by achievement track, gender, or gender composition of working groups. In an urban school district, 202 students from two eighth‐grade science classes participated in a collaborative mobile science game. Data included a self‐report survey collected after the game that measured player's flow experience. Using a regression model, the relationship of flow experience with achievement track and gender was explored while controlling for group composition and teacher effects. The study found that gender was related to flow experience; specifically, girls reported higher flow experience scores (d = 0.30). Flow experience did not have a statistically significant relationship with achievement track showing that the activity engaged all observed students similarly.     

Collaborative learning with screen‐based simulation in health care education: an empirical study of collaborative patterns and proficiency development

This article is about collaborative learning with educational computer‐assisted simulation (ECAS) in health care education. Previous research on training with a radiological virtual reality simulator has indicated positive effects on learning when compared to a more conventional alternative. Drawing upon the field of Computer‐Supported Collaborative Learning, we investigate collaborative patterns, their causes, and their implications for learning. We investigate why the extent of application of subject‐specific terminology differs between simulation training and more conventional training. We also investigate how the student‐simulator interaction affordances produce collaborative patterns and impact learning. Proficiency tests before and after training, observations during training, and interviews after training constitute the empirical foundation. Thirty‐six dentistry students volunteered for participation. The results showed that not only the task but also the medium of feedback impacts the application of subject‐specific terminology. However, no relation to proficiency development was revealed. We identified turn‐taking as well as dominance patterns of student‐simulator interaction but again found no relation to proficiency development. Further research may give us deeper insights into if and how these collaborative patterns, in other respects, impact collaborative learning with ECAS in health care education.     

Comparative analysis of Palm and wearable computers for Participatory Simulations

Abstract Recent educational computer‐based technologies have offered promising lines of research that promote social constructivist learning goals, develop skills required to operate in a knowledge‐based economy ( Roschelle et al. 2000 ), and enable more authentic science‐like problem‐solving. In our research programme, we have been interested in combining these aims for curricular reform in school science by developing innovative and progressive hand‐held and wearable computational learning tools. This paper reports on one such line of research in which the learning outcomes of two distinct technological platforms (wearable computers and Palm hand‐helds) are compared using the same pedagogical strategy of Participatory Simulations. Participatory Simulations use small wearable or hand‐held computers to engage participants in simulations that enable inquiry and experimentation ( Colella 2000 ) allowing students to act out the simulation themselves. The study showed that the newer and more easily distributable version of Participatory Simulations on Palms was equally as capable as the original Tag‐based simulations in engaging students collaboratively in a complex problem‐solving task. We feel that this robust and inexpensive technology holds great promise for promoting collaborative learning as teachers struggle to find authentic ways to integrate technology into the classroom in addition to engaging and motivating students to learn science.     

Modeling individual and collaborative problem-solving in medical problem-based learning

Today a great many medical schools have turned to a problem-based learning (PBL) approach to teaching as an alternative to traditional didactic medical education to teach clinical-reasoning skills at the early stages of medical education. While PBL has many strengths, effective PBL tutoring is time-intensive and requires the tutor to provide a high degree of personal attention to the students, which is difficult in the current academic environment of increasing demands on faculty time. This paper describes the student modeling approach used in the COMET intelligent tutoring system for collaborative medical PBL. To generate appropriate tutorial actions, COMET uses a model of each student’s clinical reasoning for the problem domain. In addition, since problem solving in group PBL is a collaborative process, COMET uses a group model that enables it to do things like focus the group discussion, promote collaboration, and suggest peer helpers. Bayesian networks are used to model individual student knowledge and activity, as well as that of the group. The validity of the modeling approach has been tested with student models in the areas of head injury, stroke, and heart attack. Receiver operating characteristic (ROC) curve analysis shows that the models are highly accurate in predicting individual student actions. Comparison with human tutors shows that the focus of group activity determined by the model agrees with that suggested by the majority of the human tutors with a high degree of statistical agreement (McNemar test, p = 0.774, Kappa = 0.823).     

An investigation of learners' collaborative knowledge construction performances and behavior patterns in an augmented reality simulation system

The purpose of this study was to investigate how a mobile collaborative augmented reality (AR) simulation system affects learners' knowledge construction behaviors and learning performances. In this study, 40 undergraduate students were recruited and divided into dyads to discuss a given task either with the assistance of a mobile collaborative AR system or traditional 2D simulation system. The participants' knowledge acquisition regarding elastic collision was evaluated through a pre-test and a post-test comparison. Learners' knowledge construction behaviors were qualitatively identified according to an adapted three-category coding scheme including construction of problem space (PS), construction of conceptual space (CS), and construction of relations between conceptual and problem space (CPS), and were then analyzed by adopting lag sequential analysis. The results indicated that the learners who learned with the AR system showed significant better learning achievements than those who learned with the traditional 2D simulation system. Furthermore, the sequential patterns of the learners' behaviors were identified, including three sustained loops (PS→PS, CS→CS, CPS→CPS), a bi-directional path between the PS and CPS activities (PS↔CPS), and a one way path from the PS activity to the CS activity (PS→CS). The revealed behavior patterns suggest that the AR Physics system may serve as a supportive tool and enable dyad learners to respond quickly to the displayed results and support their knowledge construction processes to produce a positive outcome. Based on the behavioral patterns found in this study, suggestions for future studies and further modifications to the system are proposed.