Detecting students-at-risk in computer programming classes with learning analytics from students’ digital footprints

User Modeling and User-Adapted Interaction - Different sources of data about students, ranging from static demographics to dynamic behavior logs, can be harnessed from a variety sources at Higher...     

A case study of computer gaming for math: Engaged learning from gameplay?

Employing mixed-method approach, this case study examined the in situ use of educational computer games in a summer math program to facilitate 4th and 5th graders’ cognitive math achievement, metacognitive awareness, and positive attitudes toward math learning. The results indicated that students developed more positive attitudes toward math learning through five-week computer math gaming, but there was no significant effect of computer gaming on students’ cognitive test performance or metacognitive awareness development. The in-field observation and students’ think-aloud protocol informed that not every computer math drill game would engage children in committed learning. The study findings have highlighted the value of situating learning activities within the game story, making games pleasantly challenging, scaffolding reflections, and designing suitable off-computer activities.     

Enhancing students’ botanical learning by using augmented reality

Universal Access in the Information Society - Scientific literacy is considered a crucial part of learners’ basic capacities. In primary schools, scientific literacy is generally cultivated...     

Application of remote sensing in rattan resource survey—a case study from Kerala,India

Abstract

The use of remote sensing technique in identifying probable rattan (cane) habitats in the natural forests of Kerala has been successfully demonstrated. Rattans occur as climbing palms in scattered, isolated pockets in different forest types. The heterogenous nature of the overstorey vegetation, as well as the lack of information on their tonal differentiability characterises the problems in delineating such areas from the rest of the forest. A new approach has been adopted to overcome this difficulty. Ground truth information was collected from as many locations as possible, to include all habitat conditions. A few of these data were statistically selected as Training sets for map preparation through digital image processing. The rest were used to cross-check the map and a method involving deductive and inductive analysis based on the colour signature of the overstorey vegetation applied as a key feature of this approach.     

The effects of social media on students’ behaviors; Facebook as a case study

Social networks are one of the most used communication methods of today's world. Their use in different fields has been examined in several research studies. This study aims to examine the effects of social media on student's behaviors which will mainly focus on Facebook. Whether there is a positive relationship between confidence, social media participation and social media related behaviors will also be assed with regard to using Facebook. In order to collect the primary data, a general scanning model was used to observe attitudes of high school students. The participants chosen were 362 high school students from level 9 to 12. The findings highlight that Facebook is used for communication entertainment and sharing news, pictures and songs. In addition, their Facebook profile picture is alone and students were aware that swearing is considered a form of misconduct, which is a good sign. The study also indicates that students were aware of protecting their social identity as their Facebook shares are not public. Furthermore, they respect privacy as they do not use their friend's Facebook account.     

Targeting areas for mineral exploration—a case study from Orissa,India

LANDSAT data comprising eight scenes in the northern and central part of Orissa State, in eastern India were interpreted visually for delineation of target areas for mineral exploration, Even though this area has been mapped and studied in considerable detail LANDSAT data have been found to be very useful in redefining the tectonic structure, correlation of regional features and mapping of hitherto unmapped features. Subsequently one scene (path 152 row 047) was digitally analysed and enhanced for delineation of bauxitic lateritic plateaux and for comparison with visual interpretation.     

Exploring the costs of technical debt management – a case study

Technical debt is a metaphor for delayed software maintenance tasks. Incurring technical debt may bring short-term benefits to a project, but such benefits are often achieved at the cost of extra work in future, analogous to paying interest on the debt. Currently technical debt is managed implicitly, if at all. However, on large systems, it is too easy to lose track of delayed tasks or to misunderstand their impact. Therefore, we have proposed a new approach to managing technical debt, which we believe to be helpful for software managers to make informed decisions. In this study we explored the costs of the new approach by tracking the technical debt management activities in an on-going software project. The results from the study provided insights into the impact of technical debt management on software projects. In particular, we found that there is a significant start-up cost when beginning to track and monitor technical debt, but the cost of ongoing management soon declines to very reasonable levels.     

Teaching of a computer literacy course in South Africa: A case study using traditional and co‐operative learning

Abstract

The Department of Informatics at the University of Pretoria in South Africa has been involved in a research project funded by the Foundation for Research and Development (FRD) since 1996. The main focus of this project is to establish computer‐supported co‐operative learning centres in various rural communities. The case study described in this paper discusses a part of this project that was undertaken during 1998. The paper outlines the computer literacy course where co‐operative learning and traditional learning methods were used. A discussion about co‐operative learning and traditional learning, with specific reference to the implementation of the two methods at SEIDET, is presented. An outline of the research results based on a questionnaire completed by the teachers who took part in the case study, is given. Although most of the teachers preferred the traditional and known method of teaching that was used for the MsExcel part of the course, they indicated that they have learnt more using the co‐operative learning method.     

Learning game innovations in immersive game environments: a factor analytic study of students’ learning inventory in virtual reality

Virtual Reality - The research is designed to trigger students’ game innovations and facilitate their creative learning process by providing them with a “stimulated” immersive...     

‘Big time’: An examination of temporal complexity and business value in analytics

Time is central to the purported business value of analytics. Yet, research has adopted a simplistic, ‘clock’ interpretation of time, ignoring its complex and socially embedded nature. There is also an overemphasis on analytics software and not on the people using them. Although analytics may be ‘fast’ to realise business value, it must cater to temporal complexities of organisations and people using it. Drawing on the temporality theory, this study develops temporal factors to examine the value of analytics. We also develop a research agenda that identifies opportunities to examine time, temporal personalities and other factors when people use analytics in the organisation.     

Performance-based testing for ICT skills assessing: a case study of students and teachers’ ICT skills in Finnish schools

Universal Access in the Information Society - Skills enabling and ensuring universal access to information have been investigated intensively during the past few years. The research results provide...     

Transportation planning from remote sensing—a case study of the Tuni region in Andhra Pradesh,India

Abstract

Transportation planning deals with the generation and distribution of activity along a road network. A safe, convenient and efficient movement of goods and people requires an integration of engineering, economic, environmental, political and social aspects and an optimal allocation of these activities needs to be carefully planned. Even when geotechnical aspects cause a constraint it is possible to plan a route which optimally utilises the land. Remote sensing data acquired from airbourne space platforms and engineering surveys have offered the planner a complete picture of the land and helped to identify the location and quantity of activity from method of the Moments/Trip polygon method and the allocation technique. Cost modelling technique has been used to identify the optimum route for the user, system, non-user, government and region point of view.     

Predicting aphid (Lipaphis erysimi) growth in oilseed Brassica using near surface meteorological data from NOAA TOVS—a case study

Pest infestation in crops is highly influenced by agrometeorological parameters. Weather based early warning of pest infestation is being practised using statistical and dynamic simulation models on point scale. Satellite based inputs and epidemiological models can extend the application to areas with irregular and non‐existing ground observations. The present study describes the use of National Oceanic and Atmospheric Administration TIROS (Television and InfraRed Operational Satellites) Operational Vertical Sounder (TOVS) near surface air temperature at 1430 h Local Apparent Time (LAT) over India (0900 Universal Time Code) for modelling onset, build‐up and peak aphid (Lipaphis erysimi) infestation on Indian Mustard (Brassica juncea) crop over Bharatpur and Kalyani, falling in semi‐arid and sub‐humid regions, respectively. The daily cumulative TOVS air temperature from 1 October 2001 showed high correlation (R ²: 0.99) with observed datasets. Exponential relationships were found to be the best empirical fit between TOVS cumulative air temperature (CAT_TOVS) and crop age at aphid onset (R ²: 0.7–0.99) and peak infestation (R ²: 0.91–0.95) for two stations representing semi‐arid (Bharatpur) and sub‐humid (Kalyani) agroclimatic conditions. Second order polynomial fits were found (R ²: 0.81–0.85) at both the stations between peak aphid count and CAT_TOVS at peak. Estimates of intermediate linear aphid build‐up to peak, computed using location‐specific linear growth rate (LGR) showed a higher standard error (SE) of 20% of mean at Kalyani (0–99), compared to 8% at Bharatpur (4–58). The common prediction models on linear start and peak were developed using TOVS noon time specific humidity (SPH) weighted thermal units and sowing dates. The standard error (SE) of estimated intermediate aphid‐build‐up became less: 4.5% of observed mean counts for pooled datasets with a common model, irrespective of sowing dates. The correlation between estimates and observations was 71%. The common model will be useful for general application in the absence of availability of local models.     

Optimisation of maintenance concept choice using risk-decision factor – a case study

This article is concerned with the state estimation problem for a kind of non-uniform sampling dynamic system. The system is described at a certain sampling rate in discrete form. A sensor observes the target successively, while the samples are obtained non-uniformly and the sampling points in each sampling periods may be different. To generate the optimal state estimate, state prediction and innovation are carried out step-by-step similar to Kalman filter (KF), but before innovation in each sampling period, measurements should be properly disposed and augmented. It is shown that our main results improve and extend the existing KF for which the samples are obtained multirate non-uniformly. Measurements randomly missing with Bernoulli distribution are also considered in this article. Finally, the feasibility and efficiency of the presented algorithm is illustrated by a numerical simulation example.     

The impact of big data analytics on firms’ high value business performance

Big Data Analytics (BDA) is an emerging phenomenon with the reported potential to transform how firms manage and enhance high value businesses performance. The purpose of our study is to investigate the impact of BDA on operations management in the manufacturing sector, which is an acknowledged infrequently researched context. Using an interpretive qualitative approach, this empirical study leverages a comparative case study of three manufacturing companies with varying levels of BDA usage (experimental, moderate and heavy). The information technology (IT) business value literature and a resource based view informed the development of our research propositions and the conceptual framework that illuminated the relationships between BDA capability and organizational readiness and design. Our findings indicate that BDA capability (in terms of data sourcing, access, integration, and delivery, analytical capabilities, and people’s expertise) along with organizational readiness and design factors (such as BDA strategy, top management support, financial resources, and employee engagement) facilitated better utilization of BDA in manufacturing decision making, and thus enhanced high value business performance. Our results also highlight important managerial implications related to the impact of BDA on empowerment of employees, and how BDA can be integrated into organizations to augment rather than replace management capabilities. Our research will be of benefit to academics and practitioners in further aiding our understanding of BDA utilization in transforming operations and production management. It adds to the body of limited empirically based knowledge by highlighting the real business value resulting from applying BDA in manufacturing firms and thus encouraging beneficial economic societal changes.     

Beyond binary correctness: Classification of students’ answers in learning systems

User Modeling and User-Adapted Interaction - Adaptive learning systems collect data on student performance and use them to personalize system behavior. Most current personalization techniques focus...     

Predicting customer behavior in the market-space: a study of Rayport and Sviokla’s framework

The rapidly evolving phenomenon of the World Wide Web and the creation of a new international arena for electronic commerce have expanded the possibilities for the marketing of products and services. The role played by customer behavior in the market-space is still not entirely understood and calls for investigations into the significance of customer attitudes and loyalty. In this article, a model is developed; it examines the significance of content, context, and infrastructure in determining customer loyalty. An empirical study involving 145 subjects was conducted to test this model and to gain a better understanding of the relationship between customer belief about a Web site (specifically, an e-publishing site) and customer behavior (such as attitudes toward brand and customer loyalty).The results indicate that customer attitude is influenced by belief about brand equity (value), which is affected by the content, context, and infrastructure. Customer loyalty is determined by attitude and belief about the context in which the products or services are offered. These findings provide a better understanding of customer behavior associated with Web sites in the market-space, also confirm the proposition of Rayport and Sviokla that ‘customer loyalty is developed at the context level’.     

Deploying Internet banking and e-commerce—case study of a private-sector bank in India

Over the last decade India has been one of the fastest adopters of information technology, particularly because of its capability to provide software solutions to organizations around the world. This capability has provided a tremendous impetus to the domestic banking industry in India to deploy the latest in technology, particularly in the Internet banking and e-commerce arenas. This article discusses the experiences of a private-sector bank in deploying Internet banking and e-commerce in India. Strategic alignment of business and IT strategies, planning and implementation of e-banking initiatives, and management of benefits are captured, along with key contributions to development. © 2005 Wiley Periodicals, Inc.     

Exploring users’ experiences of using personal cloud storage services: a phenomenological study

Recently, cloud computing has attracted great attention for both personal and organisational usages. Despite a large number of research conducted about cloud adoption, little is known about how users practically experienced the usage and adoption of Personal Could Storage Service (PCSSs) particularly in the context of developing countries. To address this gap, this paper seeks a clear understanding of how participants have profoundly experienced and perceived PCSSs to obtain worthwhile insights towards the essence of PCSSs’ adoption as a multifaceted phenomenon. Applying the interpretive phenomenology as a research method, required data were collected by conducting semi-structured interviews with 12 experienced participants. The results reveal that users’ intentions to adopt PCSSs are highly influenced by three emerged themes, including demand-side factors, supply-side factors, and institutional factors. Concerning the demand-side factors, the paper demonstrates how user-centric aspects work in favour of PCSSs’ adoption. As to the supply-side factors, this research promotes an understanding of how the participants have perceived tangible and non-tangible features of PCSSs as a determinant of the adoption. Regarding the formal and informal institutions, remarkable roles of regulatory environments and culture are highlighted, respectively. The theoretical and practical implications of this study are discussed for both academia and practitioners.