Learning Opportunities and Challenges of Sensor-enabled Intelligent Tutoring Systems on Mobile Platforms: Benchmarking the Reliability of Mobile Sensors to Track Human Physiological Signals and Behaviors to Enhance Tablet-Based Intelligent Tutoring Systems

Desktop-based intelligent tutoring systems have existed for many decades, but the advancement of mobile computing technologies has sparked interest in developing mobile intelligent tutoring systems (mITS). Personalized mITS are applicable to not only stand-alone and client-server systems but also cloud systems possibly leveraging big data. Device-based sensors enable even greater personalization through capture of physiological signals during periods of student study. However, personalizing mITS to individual students faces challenges. The Achilles heel of personalization is the feasibility and reliability of these sensors to accurately capture physiological signals and behavior measures. This research reviews feasibility and benchmarks reliability of basic mobile platform sensors in various student postures. The research software and methodology are generalizable to a range of platforms and sensors. Incorporating the tile-based puzzle game 2048 as a substitute for a knowledge domain also enables a broad spectrum of test populations. Baseline sensors include the on-board camera to detect eyes/faces and the Bluetooth Empatica E4 wristband to capture heart rate, electrodermal activity (EDA), and skin temperature. The test population involved 100 collegiate students randomly assigned to one of three different ergonomic positions in a classroom: sitting at a table, standing at a counter, or reclining on a sofa. Well received by the students, EDA proved to be more reliable than heart rate or face detection in the three different ergonomic positions. Additional insights are provided on advancing learning personalization through future sensor feasibility and reliability studies

First-Semester Organic Chemistry During COVID-19: Prioritizing Group Work, Flexibility, and Student Engagement

Our first-semester organic chemistry class focused on structured group work to enable active learning in class. When Smith College switched to online learning after spring break, the class was adapted to fit into an online learning model while retaining active learning. Using feedback from students, we implemented two tracks, one focused on independent work and one focused on group work. Using Zoom’s breakout rooms, we were able to simulate the full class and small group experiences of our in-person class with the help of student learning assistants to facilitate group learning. Slack was introduced for class questions and communications. Student feedback was positive overall and indicated that their perceptions about group work improved over the semester. In the case of in-person classes in the fall, this method might be preferable to a class in which social distancing hampers student-to-student discussion

Mechanix: An Intelligent Web Interface for Automatic Grading of Sketched Free-Body Diagrams

Sketching free body diagrams is an essential skill that students learn in introductory physics and engineering classes; however, university class sizes are growing and often have hundreds of students in a single class. This situation creates a grading challenge for instructors as there is simply not enough time nor resources to provide adequate feedback on every problem. We have developed a web-based application called Mechanix to provide automated real-time feedback on hand-drawn free body diagrams for students. The system is driven by novel sketch recognition algorithms developed for recognizing and comparing trusses, general shapes, and arrows in diagrams. We have discovered students perform as well as paper homework or other online homework systems which only check the final answer through deployment to five universities with 450 students completing homework on the system over the 2018 and 2019 school years. Mechanix has reduced the amount of manual grading required for instructors in those courses while ensuring students can correctly draw the free body diagram

Revisiting the Definition of a Virtual Manipulative

In 2002, Moyer, Bolyard and Spikell defined a virtual manipulative as an “an interactive, Web-based visual representation of a dynamic object that presents opportunities for constructing mathematical knowledge” (p. 373). The purpose of this chapter is to revisit, clarify and update the definition of a virtual manipulative. After clarifying what a virtual manipulative is and what it is not, we propose an updated definition for virtual manipulative: an interactive, technology-enabled visual representation of a dynamic mathematical object, including all of the programmable features that allow it to be manipulated, that presents opportunities for constructing mathematical knowledge. The chapter describes the characteristics of five of the most common virtual manipulative environments in use in education: single-representation, multi-representation, tutorial, gaming and simulation

Mobile learning: Examining the relationships between the use of mobile devices and student performance in ELA and math within technology and non-technology districts

Mobile and other internet-connected devices infiltrate society, including K-12 classrooms. A large body of research indicated that these devices might distract students; however, other studies have revealed many benefits when the devices are used for educational purposes. This study aimed to examine the relationships between the use of mobile devices and student performance in mathematics (MA) and English Language Arts (ELA). The study compared two districts, one that had implemented a 1:1 technology infrastructure for learning and one that had not. Archival data on the Mississippi Academic Assessment Program (MAAP) standardized test were accessed from the two districts, containing fourth-grade students\u27 MA and ELA scores from the assessment. Additional data included students\u27 gender and i-Ready diagnostic test scores in the 1:1 technology district. One-way analysis of variance (ANOVA) tests revealed that MAAP MA scores were significantly higher for students in the 1:1 technology district than for students in the non-technology district. However, no difference was found in students\u27 ELA scores. A Pearson\u27s rho correlation analysis indicated a significant association between i-Ready and MAAP MA and ELA scores for students in the 1:1 technology district. Linear regression analysis revealed that gender explained a small but significant variance in MAAP ELA scores across the two districts. The study provided mixed results for using mobile devices for student learning. Students may benefit more from mobile technology in mathematics than in ELA, possibly because specific mathematics skills can be isolated, taught, and practiced using technology. Additionally, because this study took place during the COVID-19 pandemic, future research should attempt to focus on mobile technology and its presence post-COVID-19. Finally, more research should explore making the most effective use of technology solutions to support student learning

Sketch Recognition on Mobile Devices

Sketch recognition allows computers to understand and model hand drawn sketches and diagrams. Traditionally sketch recognition systems required a pen based PC interface, but powerful mobile devices such as tablets and smartphones can provide a new platform for sketch recognition systems. We describe a new sketch recognition library, Strontium (SrL) that combines several existing sketch recognition libraries modified to run on both personal computers and on the Android platform. We analyzed the recognition speed and accuracy implications of performing low-level shape recognition on smartphones with touch screens. We found that there is a large gap in recognition speed on mobile devices between recognizing simple shapes and more complex ones, suggesting that mobile sketch interface designers limit the complexity of their sketch domains. We also found that a low sampling rate on mobile devices can affect recognition accuracy of complex and curved shapes. Despite this, we found no evidence to suggest that using a finger as an input implement leads to a decrease in simple shape recognition accuracy. These results show that the same geometric shape recognizers developed for pen applications can be used in mobile applications, provided that developers keep shape domains simple and ensure that input sampling rate is kept as high as possible

The Potential of Using Augmented Reality (AR) Technology as Learning Material in TVET

In the field of education today, people can choose from a variety of ways and methods to acquire specific information and skills; here are some good examples: classroom lectures with textbooks, computers, hand-held devices, and other electronics appliances such as tablets and smartphones. In a rapidly changing society, there are countless sources of knowledge and a great deal of available information; hence, adopting an appropriate method and applying relevant information at the right time and place are important in both schools and business settings. The augmented reality (AR) technology is one of the most advanced developments in the education sector tailored for 21st Century learning. With so much to offer, it is worthwhile to investigate the potential of integrating AR into the teaching-learning processes. This study focuses on exploring the possibility of merging TVET learning materials with the AR technology; the survey was carried out among the lecturers to gauge their knowledge and perception of AR as well as the relationship between the two elements. This quantitative study includes randomly selected samples of 230 lecturers from Universiti Tun Hussein Onn Malaysia (UTHM). The respondents were given a questionnaire to answer. The SPSS version 22 software package was used to analyse the data collected. Overall, the mean score indicates that the lecturers' knowledge level for AR technology is high. The lecturers also have a positive perception of using AR as a tool to incorporate and present the learning materials. Finally, this study discovers that there is a positive relationship between the lecturers’ information about AR and their perception of using AR as a vehicle to deliver the learning materials. AR is expected to achieve widespread adoption in schools, universities and colleges,  TVET and other higher learning institutions. Therefore, this study may be useful to the developers and providers of augmented reality solutions, end users of these solutions, teachers and students, and the experimenting digital communities.&nbsp

The Importance of Using Mobile Learning in Supporting Teaching and Learning of English Language in the Secondary Stage

The aim of this study is to recognize the importance of using mobile learning in supporting teaching and learning English among students at secondary stage through the identification of potential uses for smart phones and tablets, and the roles it can play in assisting the teaching and learning of English among secondary school students in the city of Mecca, from the viewpoint of the supervisors and teachers of English, also aimed to find out the presence of statistically significant differences between the mean responses of members of the study population due to the variables: nature of work, academic qualification, years of service, and number of training courses. The researcher used the descriptive survey, and the questionnaire was its tool, and was applied to all members of the study population in the city of Mecca for the first semester of the year 1435 AH, and 210 responded, by 195 teachers and 15 supervisor. After using the suitable statistical methods study reached to the following conclusions: there is a strong approval on the feasible uses of mobile learning and roles in supporting the teaching and learning of English at the secondary stage from the viewpoint of the supervisors and teachers of English, no statistically significant differences between the mean responses of study sample on possible uses for mobile learning and roles in supporting teaching and learning of English among secondary school students due to (nature of work, academic qualification , years of service), while statistically significant differences is found between the mean responses of the study sample on possible uses of mobile learning and roles in supporting the teaching and learning of English among secondary school students is due to number of training courses; in favor of members attended 16 training course of more; where the arithmetic mean of their responses is the highest. In the light of the results of the study, the researcher suggested a number of recommendations including: activate the use of mobile learning devices, and urge students to take advantage of them to support the teaching and learning of English in various stages of education, establish training courses for supervisors and teacher of English in communications and information technology and its role in supporting teaching and learning of English language

The WOZ Recognizer: A Tool For Understanding User Perceptions of Sketch-Based Interfaces

Sketch recognition has the potential to be an important input method for computers in the coming years; however, designing and building an accurate and sophisticated sketch recognition system is a time consuming and daunting task. Since sketch recognition is still at a level where mistakes are common, it is important to understand how users perceive and tolerate recognition errors and other user interface elements with these imperfect systems. A problem in performing this type of research is that we cannot easily control aspects of recognition in order to rigorously study the systems. We performed a study examining user perceptions of three pen-based systems for creating logic gate diagrams: a sketch-based interface, a WIMP-based interface, and a hybrid interface that combined elements of sketching and WIMP. We found that users preferred the sketch-based interface and we identified important criteria for pen-based application design. This work exposed the issue of studying recognition systems without fine-grained control over accuracy, recognition mode, and other recognizer properties. In order to solve this problem, we developed a Wizard of Oz sketch recognition tool, the WOZ Recognizer, that supports controlled symbol and position accuracy and batch and streaming recognition modes for a variety of sketching domains. We present the design of the WOZ Recognizer, modeling recognition domains using graphs, symbol alphabets, and grammars; and discuss the types of recognition errors we included in its design. Further, we discuss how the WOZ Recognizer simulates sketch recognition, controlling the WOZ Recognizer, and how users interact with it. In addition, we present an evaluative user study of the WOZ Recognizer and the lessons we learned. We have used the WOZ Recognizer to perform two user studies examining user perceptions of sketch recognition; both studies focused on mathematical sketching. In the first study, we examined whether users prefer recognition feedback now (real-time recognition) or later (batch recognition) in relation to different recognition accuracies and sketch complexities. We found that participants displayed a preference for real-time recognition in some situations (multiple expressions, low accuracy), but no statistical preference in others. In our second study, we examined whether users displayed a greater tolerance for recognition errors when they used mathematical sketching applications they found interesting or useful compared to applications they found less interesting. Participants felt they had a greater tolerance for the applications they preferred, although our statistical analysis did not positively support this. In addition to the research already performed, we propose several avenues for future research into user perceptions of sketch recognition that we believe will be of value to sketch recognizer researchers and application designers