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This paper outlines a proposal for the development of educational multiplayer online games based on the activity theory, as an alternative to the current trend in multiplayer gaming and a means of promoting collaboration among students. In order to examine whether online games are engaging for learners, we consider multiple factors regarding game play – such as frequency of game use, gender differences, identification with the characters, and game preferences – as well as some psychosocial factors that may influence learning – such as academic performance, self-esteem, and computer self-efficacy. This paper suggests that online multiplayer educational games should be approached as a complex learning system, based on the principles of activity theory, where the Subjects would interact with other Subjects, Objects and Tools of the game, under specified Rules and create Communities through division of labor, leading to the expected learning outcome. Thus, we suggest taking into account some important issues concerning the Subjects that the activity theory refers to, such as gender differences in playing games, academic performance, self-esteem and computer self-efficacy.
Although e-learning has been prompted to various education levels, the intention to continue using such systems is still very low, and the acceptance-discontinuance anomaly phenomenon (i.e., users discontinue using e-learning after initially accepting it) is a common occurrence. This paper synthesizes the expectation–confirmation model (ECM), the technology acceptance model (TAM), the theory of planned behavior (TPB), and the flow theory to hypothesize a theoretical model to explain and predict the users’ intentions to continue using e-learning. The hypothesized model is validated empirically using a sample collected from 363 learners of a Web-based learning program designed for continuing education. The results demonstrate that satisfaction has the most significant effect on users’ continuance intention, followed by perceived usefulness, attitude, concentration, subjective norm, and perceived behavior control as significant but weaker predictors. The implications of these findings for e-learning practitioners are discussed at the end of this work.
This paper is the first of its series that studies the power children have in game-play and examines its implications for teaching and learning. As a start, the paper describes a framework of power based on a synthesis of various types of power underlined in literature. The paper then looks into the power issue through observation and interviews of one twelve-year-old boy’s game-play. Several initial findings are delineated. Connections are made between the framework of power and different kinds of power that the twelve-year-old negotiates in playing games. The study sets a foundation for further research in the power issue in education.
A forum is a valuable tool to foster reflection in an in-depth discussion; however, it forces the course mediator to continually pay close attention in order to coordinate learners’ activities. Moreover, monitoring a forum is time consuming given that it is impossible to know in advance when new messages are going to be posted. Additionally, a forum may be inactive for a long period and suddenly receive a burst of messages forcing forum mediators to frequently log on in order to know how the discussion is unfolding to intervene whenever it is necessary. Mediators also need to deal with a large amount of messages to identify off-pattern situations. This work presents a piece of action research that investigates how to improve coordination support in a forum using mobile devices for mitigating mediator’s difficulties in following the status of a forum. Based on summarized information extracted from message meta-data, mediators consult visual information summaries on PDAs and receive textual notifications in their mobile phone. This investigation revealed that mediators used the mobile-based coordination support to keep informed on what is taking place within the forum without the need to log on their desktop computer.
We present a novel approach to the automated marking of student programming assignments. Our technique quantifies the structural similarity between unmarked student submissions and marked solutions, and is the basis by which we assign marks. This is accomplished through an efficient novel graph similarity measure (AssignSim). Our experiments show good correlation of assigned marks with that of a human marker.
This work describes a new Moodle module developed to give support to the practical content of a basic computer organization course. This module goes beyond the mere hosting of resources and assignments. It makes use of an automatic checking and verification engine that works on the VHDL designs submitted by the students. The module automatically keeps up to date information about their state, and significantly reduces the overload that a continuous assessment demands to the teacher. Additionally, this new module is oriented to promote a collaborative teamwork allowing to define student teams in a more operative way than built-in Moodle groups. The module has been designed according to the Moodle philosophy and its application can be extended to other similar subjects.
The dearth of women in technology and ICT-related fields continues to be a topic of interest for both the scientific community and decision-makers. Research on attitudes towards computers proves that women display more negative computer attitudes than men and also make less intense use of technology and computers than their male counterparts. For this reason, the main aims of this study are threefold. Firstly, to analyze the existence of gender differences in three dimensions of computer attitudes in a group of 550 secondary students in Spain (mean of age = 15 years old; SD = 1.73). Secondly, to study the moderating influence of a group of contextual variables on those gender differences in computer attitudes. And thirdly, to examine the predictive role of computer attitudes on the intention to pursue technology-related occupations. Some of the analyses of variance carried out show more positive computer attitudes in boys than in girls. These differences are more salient among students coming from rural areas and the upper social class, who are also enrolled in the domain of technology in secondary education, and whose mothers have no occupation outside the home. Finally, simple logistic regressions were carried out in order to prove that all dimensions of computer attitudes predict the enrollment intentions to pursue technology-related occupations. Nonetheless, gender only moderates the relationship between the cognitive dimension of computer attitudes and the enrollment intentions to pursue technology-related occupations.
Earlier studies have suggested that higher education institutions could harness the predictive power of Learning Management System (LMS) data to develop reporting tools that identify at-risk students and allow for more timely pedagogical interventions. This paper confirms and extends this proposition by providing data from an international research project investigating which student online activities accurately predict academic achievement. Analysis of LMS tracking data from a Blackboard Vista-supported course identified 15 variables demonstrating a significant simple correlation with student final grade. Regression modelling generated a best-fit predictive model for this course which incorporates key variables such as total number of discussion messages posted, total number of mail messages sent, and total number of assessments completed and which explains more than 30% of the variation in student final grade. Logistic modelling demonstrated the predictive power of this model, which correctly identified 81% of students who achieved a failing grade. Moreover, network analysis of course discussion forums afforded insight into the development of the student learning community by identifying disconnected students, patterns of student-to-student communication, and instructor positioning within the network. This study affirms that pedagogically meaningful information can be extracted from LMS-generated student tracking data, and discusses how these findings are informing the development of a customizable dashboard-like reporting tool for educators that will extract and visualize real-time data on student engagement and likelihood of success.
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