Yin-Leng Theng

Mobile G-Portal supporting collaborative sharing and learning in geography fieldwork: an empirical study

Integrated with G-Portal, a Web-based geospatial digital library of geography resources, this paper describes the implementation of Mobile G-Portal, a group of mobile devices as learning assistant tools supporting collaborative sharing and learning for geography fieldwork. Based on a modified Technology Acceptance Model and a Task-Technology Fit model, an initial study with Mobile G-Portal was conducted involving 39 students in a local secondary school. The findings suggested positive indication of acceptance of Mobile G-Portal for geography fieldwork. The paper concludes with a discussion on technological challenges, recommendations for refinement of Mobile G-Portal, and design implications in general for digital libraries and personal digital assistants supporting mobile learning.

Game-Based Digital Interventions for Depression Therapy: A Systematic Review and Meta-Analysis

The aim of this study was to review the existing literature on game-based digital interventions for depression systematically and examine their effectiveness through a meta-analysis of randomized controlled trials (RCTs). Database searching was conducted using specific search terms and inclusion criteria. A standard meta-analysis was also conducted of available RCT studies with a random effects model. The standard mean difference (Cohens d) was used to calculate the effect size of each study. Nineteen studies were included in the review, and 10 RCTs (eight studies) were included in the meta-analysis. Four types of game interventions-psycho-education and training, virtual reality exposure therapy, exercising, and entertainment-were identified, with various types of support delivered and populations targeted. The meta-analysis revealed a moderate effect size of the game interventions for depression therapy at posttreatment (d=-0.47 [95% CI -0.69 to -0.24]). A subgroup analysis showed that interventions based on psycho-education and training had a smaller effect than those based on the other forms, and that self-help interventions yielded better outcomes than supported interventions. A higher effect was achieved when a waiting list was used as the control. The review and meta-analysis support the effectiveness of game-based digital interventions for depression. More large-scale, high-quality RCT studies with sufficient long-term data for treatment evaluation are needed.

Math information retrieval: user requirements and prototype implementation

We report on the user requirements study and preliminary implementation phases in creating a digital library that indexes and retrieves educational materials on math. We first review the current approaches and resources for math retrieval, then report on the interviews of a small group of potential users to properly ascertain their needs. While preliminary, the results suggest that meta-search and resource categorization are two basic requirements for a math search engine. In addition, we implement a prototype categorization system and show that the generic features work well in identifying the math contents from the webpage but perform less well at categorizing them. We discuss our long term goals, where we plan to investigate how math expressions and text search may be best integrated.

Dynamic digital libraries for children

The majority of current digital libraries (DLs) are not designed forchildren. For DLs to be popular with children, they need to be fun, easy-to-use and empower them, whether as readers or authors. This paper describes a new childrens DL emphasizing its design and evaluation, working with the children (11-14 year olds) as design partners and testers. A truly participatory process was used, and observational study was used as a means of refinement to the initial design of the DL prototype. In contrast with current DLs, the childrens DL provides both a static as well as a dynamic environment to encourage active engagement of children in using it. Design, implementation and security issues are also raised.

Wii as entertainment and socialisation aids for mental and social health of the elderly

As the world population ages rapidly, it is likely that more elderly risks being detached from society. The possible isolation of many more elderly could lead to societal and mental health problems that could weigh down on public healthcare systems. Using surveys, focus groups, interviews and video analysis, our pilot study examines the effects of the Nintendo Wii games, examples of co-located games, between two generations (old and young), and the factors that could affect the adoption and enjoyment of computer-mediated games as entertainment and socialization aids between the elderly and the youths. This pilot study with 14 pairs of elderly-teenager participants shows that general attitude towards the other age group improves after a period of playing. The paper concludes with a discussion on design recommendations for computer-mediated games in general that can support inter-generational gameplay between the elderly and the youths, and as entertainment and socialisation aids to promote positive mental and social health of the elderly.

GeogDL: a web-based approach to geography examination revision

Social interactions profoundly impact the learning processes of learners in traditional societies. The rapid rise of the Internet using population has been the establishment of numerous different styles of network communities. Network societies form when more Internet communities are established, but the basic form of a network society, especially a network learning society, remains unclear. In 1998, a group of Taiwanese researchers created a network learning society, named ‘‘EduCities’’. Based on the experience of building this network learning society, the authors found that a structured network learning society architecture helps participants to coordinate and manage interaction processes. This study describes 10 basic elements involved in establishing a structured network learning society, i.e., participants, shared visions, devices, services, rules, relations, manners, learning domains, learning goals and learning activities. A structured network learning society environment, ‘‘EduCities’’, was then implemented based on the structured network learning society concept. EduCities included numerous structural designs, including EduCity, EduTown, EduSisterTown, EduVillage, EduSisterVillage, EduCitizen, and EduHome were practiced. Participants in EduCities own their roles, managing power, learning goals, and social relations. The structured network learning society concept represents a prototype of an online learning society. 2005 Elsevier Ltd. All rights reserved.

The Use of Videogames, Gamification, and Virtual Environments in the Self-Management of Diabetes: A Systematic Review of Evidence

The use of videogames in healthcare interventions is gaining popularity, but there is still a gap in the understanding on how these types of interventions are used for the management of diabetes. The purpose of this review is to examine published research on the use of videogames for diabetes management. With the increased use of mobile technology, the review was expanded to understand whether games, gamification, and virtual environments can be used for diabetes self-management. Out of the 307 articles identified, only 10 articles met the inclusion criteria of the study. The duration of most studies was short, with small sample sizes. All interventions targeted behavioral changes examining risk reduction of diabetes-related risk and promotion of healthy behavior among study participants. Videogames appeared to be helpful tools for education in some interventions, whereas gamification and virtual environments increased extrinsic motivation and provided positive reinforcement. This review concludes by discussing the potential of using videogames and gamification for the self-management of diabetes.

Sentiment lexicons for health-related opinion mining

Opinion mining consists in extracting from a text opinions expressed by its author and their polarity. Lexical resources, such as polarized lexicons, are needed for this task. Opinion mining in the medical domain has not been well explored, partly because little credence is given to patients and their opinions (although more and more of them are using social media). We are interested in opinion mining of user-generated content on drugs/medication. We present in this paper the creation of our lexical resources and their adaptation to the medical domain. We first describe the creation of a general lexicon, containing opinion words from the general domain and their polarity. Then we present the creation of a medical opinion lexicon, based on a corpus of drug reviews. We show that some words have a different polarity in the general domain and in the medical one. Some words considered generally as neutral are opinionated in medical texts. We finally evaluate the lexicons and show with a simple algorithm that using our general lexicon gives better results than other well-known ones on our corpus and that adding the domain lexicon improves them as well.

Sentence-level sentiment polarity classification using a linguistic approach

Recent sentiment analysis research has focused on the functional relations of words using typed dependency parsing as this provides a refined analysis on the grammar and semantics of the textual data, which could improve performance. However, typed dependencies only provide the grammatical relationships between individual words while there exist more complex relationships between words that could influence a sentence sentiment polarity. In this paper, we propose a linguistic approach, called Polarity Prediction Model (PPM), that combines typed dependencies and subjective phrase analysis to detect sentence-level sentiment polarity. Our approach also considers the intensity of words and domain terms that could influence the sentiment polarity output. PPM is shown to provide a fine-grained analysis for handling and explaining the complex relationships between words in detecting a sentence sentiment polarity. PPM was found to consistently outperform a baseline model by 5% in terms of overall F1-score, and exceeding 10% in terms of positive F1- score when compared to a Typed-dependency only approach.

Lessons from learner experiences in a field-based inquiry in geography using mobile devices

Geographical inquiry involves collecting, using and making sense of the data to investigate some geographical phenomena. With the increasing number of mobile devices equipped with Internet access capabilities, there is a wide scope for using it in field inquiry where learning can take place in the form of social interactions between team members while performing a common task. The authors examine the use of MobiTOP (Mobile Tagging of Objects and People), a geospatial digital library system which allows users to contribute and share multimedia annotations via mobile devices, within a geographical field inquiry. A key feature of MobiTOP that is well suited for collaborative learning is that annotations are hierarchical, allowing annotations to be annotated by other users to an arbitrary depth. A group of student and teachers involved in an inquiry-based learning activity in geography was instructed to identify rock types and associated landforms by collaborating with each other using the MobiTOP system. A method combining several data collection methods was used. Four main findings on the affordances of the mobile phone, the need for specialized training in using the application with the mobile phone, design considerations of the application and the authentic context of learning with fieldwork are reported. A discussion on the implication of these findings and how mobile technology may be used for geographical field learning are also included in this paper.