THE EYES HAVE IT: USING EYE TRACKING TECHNOLOGY TO ASSESS THE USABILITY OF LEARNING MANAGEMENT SYSTEMS IN ELEMENTARY SCHOOLS

Twenty-six students from a sixth grade math class in Upstate New York received guardian approval to participate in a study that gathered data pertaining to student navigation ability, information retrieval ability, and satisfaction in regards to the Learning Management System (LMS) their school utilized. Data collection began with the researchers attending math classes for observation and to conduct cognitive walkthroughs with the students to gather information about their experiences and navigation through the LMS. An eye tracker and the associated eye tracking software were utilized to monitor and detect patterns of eye movements when the students were looking at a device screen. For this study, students were monitored by the eye tracker while they attempted to complete several tasks from the experiment. By measuring the length of time taken by students as they completed tasks on the LMS, quantitative data can be collected and used later in the experiment. After analyzing the time metrics and the eye tracking data produced and feedback given on the questionnaire distributed at the beginning of the experiment, a targeted LMS page was slightly modified in hopes to increase the effectiveness of the page, based on user interface design standards.  Well defined organization, accessibility, and usability in an LMS is essential to allow learners to focus to be on their curriculums, and not how to access their assignments. An in-depth analysis of navigation through an LMS will allow for a better understanding of how users interact with the structure of their curriculum in an electronic format. The study described in this paper intended to address the question of whether an LMS used in an elementary school setting can provide users with an interface that optimizes the accessibility and usability of their class materials.  Article visualizations

THE EYES HAVE IT: USING EYE TRACKING TECHNOLOGY TO ASSESS THE USABILITY OF LEARNING MANAGEMENT SYSTEMS IN ELEMENTARY SCHOOLS

Twenty-six students from a sixth grade math class in Upstate New York received guardian approval to participate in a study that gathered data pertaining to student navigation ability, information retrieval ability, and satisfaction in regards to the Learning Management System (LMS) their school utilized. Data collection began with the researchers attending math classes for observation and to conduct cognitive walkthroughs with the students to gather information about their experiences and navigation through the LMS. An eye tracker and the associated eye tracking software were utilized to monitor and detect patterns of eye movements when the students were looking at a device screen. For this study, students were monitored by the eye tracker while they attempted to complete several tasks from the experiment. By measuring the length of time taken by students as they completed tasks on the LMS, quantitative data can be collected and used later in the experiment. After analyzing the time metrics and the eye tracking data produced and feedback given on the questionnaire distributed at the beginning of the experiment, a targeted LMS page was slightly modified in hopes to increase the effectiveness of the page, based on user interface design standards. Well defined organization, accessibility, and usability in an LMS is essential to allow learners to focus to be on their curriculums, and not how to access their assignments. An in-depth analysis of navigation through an LMS will allow for a better understanding of how users interact with the structure of their curriculum in an electronic format. The study described in this paper intended to address the question of whether an LMS used in an elementary school setting can provide users with an interface that optimizes the accessibility and usability of their class materials

Technology Corner: Visualising Forensic Data: Evidence Guidelines (Part 2)

Visualisation is becoming increasingly important for understanding information, such as investigative data (for example: computing, medical and crime scene evidence) and analysis (for example, network capability assessment, data file reconstruction and planning scenarios). Investigative data visualisation is used to reconstruct a scene or item and is used to assist the viewer (who may well be a member of the general public with little or no understanding of the subject matter) to understand what is being presented. Analysis visualisations, on the other hand, are usually developed to review data, information and assess competing scenario hypotheses for those who usually have an understanding of the subject matter. Courtroom environments are morphing into cinematic display environments, the media consumed by an audience who are increasingly visually literate and media savvy (Heintz, 2002). There are a number of fundamental implications inherent in the shift from oral to visual mediation and a number of facets of this modern evidence presentation technology needs to be investigated and analysed. One of the primary issues of visualisation is that no matter how coherent the data, there will always be conjecture and debate as to how the information is/has-been visualised and, is it presented in an acceptable and meaningful way. This paper presents a range of examples of where forensic data has been visualised using various techniques and technology, the paper then examines aspects of the visual courtroom evidence presented and discusses some of the benefits and potential problems of implementing this technology. This paper is part two of a two-part series that aims to describe the use of, and provide guidelines for, the use of graphical displays in courtrooms

Surface mine design using intelligent computer techniques

Surface mine planning involves the results of algorithmic numerical calculations being used by engineers to make informed decisions relating to the design. The Department of Mining Engineering at the Unversity of Nottingham has in the past been involved in developing modular algorithmic packages. The emphasis of the computer research has now altered. Smaller specialised systems are now being developed to cover individual aspects of the design process. Artificial intelligence techniques are being introduced into the mining environment to solve the planning problems often associated with the large amounts of uncertain information needed by the engineer. This thesis is concerned with the development of MINDER, a decision support system capable of assisting the mine planner in the complex task of optimum surface mining equipment selection. An expert system shell has been used to create a series of individual application modules, each containing a multi-level knowledge base structure. An information handling system has been developed which is capable of storing consultation information and transfering it between knowledge bases and between application modules. Once an effective method of information handling had been achieved the flow of control between the system knowledge bases was rapid and followed complex inferencing routes. Most of the commercially available packages mathematically model a deposit, calculate volumes and simulate operations. One of the aims of the MINDER system was to integrate with other software, for example MINDER is capable of reading volumetric and material information from Surpac mine planning software. Geological data and manufacturer’s equipment specifications are stored in DbaseIV databases. The expert system is capable of writing macros based on the consultation and performing complex relation operations involved in the elimination and ranking of equipment. In a similar manner macros are written to control the simulation package GPSS which used to simulate operations using the selected equipment. A range of ‘in-house’ Pascal software is used for numerical calculations and matrix manipulation, an example of this is the fuzzy logic software used to handle uncertain information. Another aspect of the project is an investigation into the use of machine learning techniques in the field of equipment selection. Knowledge induction software has been used to induce new rules and check those produced in the MINDER system. Various experiments have been carried out using neural network software to produce equipment selection models. Training data taken from the mining industry was used on both these systems and the results were tested against MINDER consultation results

Surface mine design using intelligent computer techniques

Surface mine planning involves the results of algorithmic numerical calculations being used by engineers to make informed decisions relating to the design. The Department of Mining Engineering at the Unversity of Nottingham has in the past been involved in developing modular algorithmic packages. The emphasis of the computer research has now altered. Smaller specialised systems are now being developed to cover individual aspects of the design process. Artificial intelligence techniques are being introduced into the mining environment to solve the planning problems often associated with the large amounts of uncertain information needed by the engineer. This thesis is concerned with the development of MINDER, a decision support system capable of assisting the mine planner in the complex task of optimum surface mining equipment selection. An expert system shell has been used to create a series of individual application modules, each containing a multi-level knowledge base structure. An information handling system has been developed which is capable of storing consultation information and transfering it between knowledge bases and between application modules. Once an effective method of information handling had been achieved the flow of control between the system knowledge bases was rapid and followed complex inferencing routes. Most of the commercially available packages mathematically model a deposit, calculate volumes and simulate operations. One of the aims of the MINDER system was to integrate with other software, for example MINDER is capable of reading volumetric and material information from Surpac mine planning software. Geological data and manufacturer’s equipment specifications are stored in DbaseIV databases. The expert system is capable of writing macros based on the consultation and performing complex relation operations involved in the elimination and ranking of equipment. In a similar manner macros are written to control the simulation package GPSS which used to simulate operations using the selected equipment. A range of ‘in-house’ Pascal software is used for numerical calculations and matrix manipulation, an example of this is the fuzzy logic software used to handle uncertain information. Another aspect of the project is an investigation into the use of machine learning techniques in the field of equipment selection. Knowledge induction software has been used to induce new rules and check those produced in the MINDER system. Various experiments have been carried out using neural network software to produce equipment selection models. Training data taken from the mining industry was used on both these systems and the results were tested against MINDER consultation results

Roman portraiture and biometric identification

This project utilised three-dimensional scanning technology in the study of ancient Roman art and archaeology: Roman representations of faces executed in marble. In the cultural heritage sector, three-dimensional (3D) scanning finds its primary application in documenting and reconstructing objects and structures mostly of simple geometry: bones, pottery, architecture or the imprint of whole archaeological sites (Adolf 2011). In forensic science, the face is interesting from investigative and probative perspectives, including both recognition and identification. Biometric methods of facial recognition have been part of a plethora of computer science-based applications used in the verification of identity (Davy et al. 2005, Goodwin, Evison and Schofield 2010). The aim of this initial project is to provide objective relevant measurements of key facial features from the two ancient Roman portrait statue three-dimensional scans, which will allow the delineation of relationships between individual portraits including formal and stylistics aspects. The work described in this paper proposal is truly multidisciplinary, it touches on many fields including : Classical archaeologies (specifically ancient art history in the period of the Roman Empire 31BC - AD400), Forensic Anthropology (specifically physical anthropology and human osteology, Facial Biometrics (specifically uniquely recognising humans based upon their intrinsic physical traits and features) and Computer Science and Statistics (specifically the analysis of large complex multi-dimensional data sets)

Roman portraiture and biometric identification

This project utilised three-dimensional scanning technology in the study of ancient Roman art and archaeology: Roman representations of faces executed in marble. In the cultural heritage sector, three-dimensional (3D) scanning finds its primary application in documenting and reconstructing objects and structures mostly of simple geometry: bones, pottery, architecture or the imprint of whole archaeological sites (Adolf 2011). In forensic science, the face is interesting from investigative and probative perspectives, including both recognition and identification. Biometric methods of facial recognition have been part of a plethora of computer science-based applications used in the verification of identity (Davy et al. 2005, Goodwin, Evison and Schofield 2010). The aim of this initial project is to provide objective relevant measurements of key facial features from the two ancient Roman portrait statue three-dimensional scans, which will allow the delineation of relationships between individual portraits including formal and stylistics aspects. The work described in this paper proposal is truly multidisciplinary, it touches on many fields including : Classical archaeologies (specifically ancient art history in the period of the Roman Empire 31BC - AD400), Forensic Anthropology (specifically physical anthropology and human osteology, Facial Biometrics (specifically uniquely recognising humans based upon their intrinsic physical traits and features) and Computer Science and Statistics (specifically the analysis of large complex multi-dimensional data sets)

Running virtual: The effect of virtual reality on exercise

Research has shown that exercise among college aged persons has dropped over recent years (Lindahl, 2015; Sheppard, 2016). Many factors could be contributing to this reduction in exercise including: large workloads, the need to work during school, or perhaps technology use. A number of recent studies are showing the benefits of using virtual reality systems in exercise and are demonstrating that the use of such technology can lead to an increase in the number of young adults engaging in exercise. This study focuses on the effects that virtual reality has on heart rate and other bodily sensations during a typical work out. This study also analyses the participants ability to pay less attention to their bodily sensations during exercise when using a virtual reality system. During this experiment, participants were exposed to two different conditions. Condition one being a traditional work out, riding an exercise bike at a middle tension level. Condition two was the same but the participant was wearing a virtual reality headset. The data collected led to the conclusion that working out while wearing a virtual reality headset will lead to a higher heart rate, and in turn can lead to burning more calories during a workout. The study also found participants who wore the virtual reality headset were able to remove themselves from their bodily sensations allowing them to workout longer