Mona Masood

Assessment of instructors’ readiness for implementing e-learning in continuing medical education in Iran

Back ground: E-learning provides new levels of flexibility in learning and teaching. This contribution of e-learning is dependent on the levels of readiness in several critical factors particularly in an educational organization. Aim: The purpose of this study was to assess instructors’ readiness and to identify the most important factors that affect their readiness in e-learning in CME programs in order to use the effective opportunities that facilitate e-learning in CME programs. Methods: A 5-point Likert scale instrument consisting of two domains (technical and pedagogical) was constructed according to four subdomains (knowledge, attitude, skills, and habits) and distributed to 70 faculty members. A factor analysis was employed to extract significant factors. Results: The results revealed that the mean of readiness on e-learning for faculty members was 3.25 ± 0.58 in technical and 3.37 ± 0.49 in pedagogical domains on a 5-point Likert scale (1–5). The factors such as “familiarity with learning management system,” “willingness to teach by adopting a new technology,” “willingness to use e-learning as a viable alternative,” “ability to deliver e-material and to provide e-content for teaching,” and “being accustomed to the virtual environment and utilization of the computer and the internet” were extracted on technical readiness domain. In addition, the pedagogical readiness factors were: “familiarity with online teaching principle and method,” “willingness to use technology in instruction and material development,” “ability to design content for e-material and online course evaluation,” and “being accustomed to providing information back up regularly and employing eclectic methods and multiple approaches in teaching.” Conclusion: The findings of this study suggest that training should be offered to instructors on a continuous, rather than a one-off basis so that their IT knowledge and skills are upgraded over time. In addition, results indicate that pedagogical innovations are required to develop and implement an effectiveness e-learning program.

Development of ICT Instructional Materials based on Needs Identified by Malaysian Secondary School Teachers

For the last few years school teachers in Malaysia have access to ICT tools in their schools. However, these tools are used mostly for record keeping and word processing purposes. An in-depth study to identify the problems of using ICT in the classroom is currently being done to elicit information concerning the needs of secondary school teachers in the Northern region of Malaysia. This research-in-progress paper discusses the needs analysis phase of the study. The teachers were asked to identify their needs in becoming competent users of ICT in the classroom; the result from this study will be used to create specific topics that will be made accessible on-line to be shared by teachers in Malaysia. The ultimate aim of this study is to develop reusable instructional material in the form of learning objects.

An eye-tracking study on the effect of infographic structures on viewer’s comprehension and cognitive load

The basic premise of this research is investigating the effect of layout on the comprehension and cognitive load of the viewers in the information graphics. The term ‘Layout’ refers to the arrangement and organization of the visual and textual elements in a graphical design. The experiment conducted in this study is designed based on two stories and each one of these stories is presented with two different layouts. During the experiment, eye-tracking devices are applied to collect the gaze data including the eye movement data and pupil diameter fluctuation. In the research on the modification of the layouts, contents of each story are narrated using identical visual and textual elements. The analysis of eye-tracking data provides quantitative evidence concerning the change of layout in each story and its effect on the comprehension of participants and variation of their cognitive load. In conclusion, it can be claimed that the comprehension from the zigzag form of the layout was higher with a less imposed cognitive load.

Visualization of invariant bot behavior for effective botnet traffic detection

Due to the sharp rise in computer network attacks through botnets, current security monitoring tools will be insufficient for effective botnet traffic detection. In fact, most of the existing tools are text-based and there is a lack of effective user friendly interface that can facilitate detection of botnet traffic in large datasets. Moreover, most of these tools are based on reactive approaches and will be triggered only after an attack is detected. Therefore, enhancement of botnet traffic detection is highly demanded. Knowledge discovery through information visualization is an avenue to solve these issues effectively. The aim of this research is to propose a proactive approach by adopting proper visualization techniques to increase the visibility of network traffic related to invariant bot behavior and botnet activities. The visualization techniques used in this research consist of graphs, scatter plots, and histograms. These visualization techniques are easy to interpret and good for visualizing large datasets. By adopting these techniques for invariant bot behavior visualization, it is possible to provide visual notification of bot existence in a network without distracting the user with huge volumes of data. In fact, the visual illustration of typical bot behavior improves the botnet traffic detection process by engaging human perception and intellectual capabilities. Overall, this visual approach can assist the security personnel to proactively detect invariant bot behaviors and botnet activities during the benign state of a botnet by providing a graphical user friendly interface. Exploiting the visual information, human analysts and security personnel will be able to gain more insights into their networks, leading to make correct decisions in critical situations and to prevent catastrophic botnet attacks.

An Eye Tracking Experiment on Strategies to Minimize the Redundancy and Split Attention Effects in Scientific Graphs and Diagrams

The focus of this study is investigating efficiency of coding and grouping methods in reducing split attention effect in scientific graphs and diagrams by applying local changes in the structure of scientific materials. The diagrams and graphs are regularly used in the structure of materials along with textual explanation to provide supplementary information and insight to the readers and is referred as redundancy principle. In some cases, the redundant presentation of visual and textual content could lead to split attention effect and cognitive overload. Although, multimedia learning theory claims that in order to enhance learning, information should be presented in multi-mode format the design and implementation of the multi-modal presentation is of great importance. Having incredible flexibility, if multimedia elements are not applied properly, they cause confusion and adversely affect comprehension of the readers.

Semiotic Differences of Macintosh Os X & Microsoft Windows 7 Based on Metaphors and Interpretation

this study utilized the Souzas semiotic engineering theory of HCI to user interface metaphors. The main aim of using Metaphors is the ability to determine the potential meaning in ongoing cognitive activities. The data were collected through the “Icon Recognition Test” and the interview questions. In addition, the users’ navigation through Mac and Win7 operating systems include certain categories of metaphors. The examination result indicated that 90% of the “structure metaphors” appeared for the desktop icons and some of the Power Point environment. The findings of the study indicated that Win7 and Mac users did not recognize their system metaphors, which reflects how users can transfer their skills and experience through and across the two platforms after one week of practice across the systems.

Learning material recommendation based on case-based reasoning similarity scores

A personalized learning material recommendation is important in any Intelligent Tutoring System (ITS). Case-based Reasoning (CBR) is an Artificial Intelligent Algorithm that has been widely used in the development of ITS applications. This study has developed an ITS application that applied the CBR algorithm in the development process. The application has the ability to recommend the most suitable learning material to the specific student based on information in the student profile. In order to test the ability of the application in recommending learning material, two versions of the application were created. The first version displayed the most suitable learning material and the second version displayed the least preferable learning material. The results show the application has successfully assigned the students to the most suitable learning material.

Real-Time Cognitive Load Measurement for Dynamic Modality Selection Using Eye-Tracking Methods

The main concern of this study is designing a framework in which the instructional material whether visual or aural can be presented in accordance with the cognitive capabilities and limitations of the learner. One of the main issues in the simultaneous application of aural and visual modalities is the amount of the capacity of the working memory of the learners and difference between the speed of integration of verbal and visual modalities in the working memory. Therefore, the existence of a dynamic system that can provide an estimation of the cognitive load of the user in the real-time could help the instructor in the presentation of the material.

Design issues and challenges for web-based history learning system for adolescents in Malaysia

In the first section of this paper, we discussed the challenges and issues in designing and developing a web-based history learning system, namely Chrono-Map Web-based Learning System for secondary school students in Malaysia. In section two, we described the main contribution of this paper, the communicability of the learning sites for adolescent which are form four secondary school students aged from 16 to 17 years old in which specific features such as digital cultural marker was included. At the end of the section, the evaluation methods such as the selection of sample size and respondents in the secondary school in a multicultural and multiracial community were discussed.

Case-Based Reasoning and Profiling System for Learning Mathematics (CBR-PROMATH)

This paper discusses the architecture of a case-based reasoning profiling system for learning mathematics (CBR-PROMATH). The adaptive system has the ability to suggest suitable learning materials based on previous cases of learner profiles and individual learning styles. The developed learning materials use a learning tool which consists of so-called mastery, understanding, interpersonal and self-expressive styles. Two sets of experiments were carried out to test the system’s functionality. The first consisted of 10 sets of learners’ profile cases, stored previously in the database. The second presented the system with 10 real new cases. The system compared and calculated similarity values between the new and stored cases. The learning material that was most similar was presented as a solution for the new case. The experiment showed that the CBR algorithm was successfully applied in the development of the CBR-PROMATH.