Cengiz Acartürk

Reducing the spatial distance between printed and online information sources by means of mobile technology enhances learning: Using 2D barcodes

Online information sources, such as pictures and animations on web pages are frequently used for complementing printed course material in educational contexts. The concurrent use of online and printed information sources by students, however, requires going back and forth between physically separated course material, such as a course book and a computer screen, thus leading to suboptimal learning outcomes. Compatible with the principles identified by the recent theoretical frameworks for multimedia learning, mobile technology provides learners with the opportunity to bring online and printed course material close together. Mobile phones make online information available within a small desktop space, in close proximity to printed course material. The challenges that are relevant to text input methods can be overcome by the 2D barcode technology. This study investigates the use of camera-equipped mobile phone and 2D barcode technology as an alternative to the use of computer screen for complementing printed course material. The results of the experimental investigation suggest that, by facilitating the access to online information sources by 2D barcode tags on course books, mobile phones have the potential to enhance learning.

A comparative analysis of global and national university ranking systems

Recent interest towards university rankings has led to the development of several ranking systems at national and global levels. Global ranking systems tend to rely on internationally accessible bibliometric databases and reputation surveys to develop league tables at a global level. Given their access and in-depth knowledge about local institutions, national ranking systems tend to include a more comprehensive set of indicators. The purpose of this study is to conduct a systematic comparison of national and global university ranking systems in terms of their indicators, coverage and ranking results. Our findings indicate that national rankings tend to include a larger number of indicators that primarily focus on educational and institutional parameters, whereas global ranking systems tend to have fewer indicators mainly focusing on research performance. Rank similarity analysis between national rankings and global rankings filtered for each country suggest that with the exception of a few instances global rankings do not strongly predict the national rankings.

The analysis of feature selection methods and classification algorithms in permission based Android malware detection

Android mobile devices have reached a widespread use since the past decade, thus leading to an increase in the number and variety of applications on the market. However, from the perspective of information security, the user control of sensitive information has been shadowed by the fast development and rich variety of the applications. In the recent state of the art, users are subject to responding numerous requests for permission about using their private data to be able run an application. The awareness of the user about data protection and its relationship to permission requests is crucial for protecting the user against malicious software. Nevertheless, the slow adaptation of users to novel technologies suggests the need for developing automatic tools for detecting malicious software. In the present study, we analyze two major aspects of permission-based malware detection in Android applications: Feature selection methods and classification algorithms. Within the framework of the assumptions specified for the analysis and the data used for the analysis, our findings reveal a higher performance for the Random Forest and J48 decision tree classification algorithms for most of the selected feature selection methods.

Towards designing audio assistance for comprehending haptic graphs: a multimodal perspective

Statistical graphs, such as line graphs are widely used in multimodal communication settings. Language accompanies graphs and humans produce gestures during the course of communication. For visually impaired people, haptic-audio interfaces provide perceptual access to graphical representations. The local and sequential character of haptic perception introduces limitations in haptic perception of hard-to-encode information, which can be resolved by providing audio assistance. In this article we first present a review of multimodal interactions between gesture, language and graphical representations. We then focus on methodologies for investigating hard-to-encode information in graph comprehension. Finally, we present a case study to provide insight for designing audio assistance.

Read That Article: Exploring Synergies between Gaze and Speech Interaction

Gaze information has the potential to benefit Human-Computer Interaction (HCI) tasks, particularly when combined with speech. Gaze can improve our understanding of the user intention, as a secondary input modality, or it can be used as the main input modality by users with some level of permanent or temporary impairments. In this paper we describe a multimodal HCI system prototype which supports speech, gaze and the combination of both. The system has been developed for Active Assisted Living scenarios.

URAP-TR: a national ranking for Turkish universities based on academic performance

This study describes the basic methodological approach and the results of URAP-TR, the first national ranking system for Turkish universities. URAP-TR is based on objective bibliometric data resources and includes both size-dependent and size-independent indicators that balance total academic performance with performance per capita measures. In the context of Turkish national university rankings, the paper discusses the implications of employing multiple size-independent and size-dependent indicators on national university rankings. Fine-grained ranking categories for Turkish universities are identified through an analysis of ranking results across multiple indicators.

Towards a systematic understanding of graphical cues in communication through statistical graphs

Statistical graphs-in particular, line graphs and bar graphs-are efficient means of communication in a wide range of non-expert settings. In communication settings, statistical graphs do not only serve as visualizations of individual data points but also provide visual access to various aspects of the information contained in data. Moreover, specific types of graphs are better means for providing visual access to certain aspects of data. For instance, trend information is visually conveyed through line graphs and bar graphs in the time domain. The interpretation of the information content in a graph is influenced by several factors, such as perceptual salience of line segments in a line graph. In addition, the presence of graphical cues substantially influences the interpretation of graph readers. Graphical cues are visual elements, usually in the form of point markers, non-directional lines, curves and arrows. They play a communicative role in communication through graphs. The present study reports an experimental investigation, in which the participants provided verbal descriptions of a set of graphs with/without graphical cues. The stimuli involved line graphs and bar graphs that represented the same data. The analyses of eye movements and verbal protocols reveal that the interpretations of the participants are systematically influenced by the presence or absence of a graphical cue, the type of the graphical cue (i.e., a point marker vs. an arrow), as well as the type of the graph (i.e., a line graph vs. a bar graph).

Points, lines and arrows in statistical graphs

Widely used statistical graphs (such as line graphs and bar graphs) are usually accompanied by graphical entities other than the graph proper. Those graphical cues, such as point marks and arrows serve for communicative purposes by bringing certain aspects to the foreground over the others. The present study discusses the results of an experimental investigation, in which the participants produced sketches of graphical cues on different types of graphs, given sentential expressions of states and processes. The outcomes of the study have the potential for serving as guidelines for the development of software tools that produce graphical cues.

Causal Inference in Graph-Text Constellations: Designing Verbally Annotated Graphs

Multimodal documents combining language and graphs are wide-spread in print media as well as in electronic media. One of the most important tasks to be solved in comprehending graph-text combinations is construction of causal chains among the meaning entities provided by modalities. In this study we focus on the role of annotation position and shape of graph lines in simple line graphs on causal attributions concerning the event presented by the annotation and the processes (i.e. increases and decreases) and states (no-changes) in the domain value of the graphs presented by the process-lines and state-lines. Based on the experimental investigation of readers’ inferences under different conditions, guidelines for the design of multimodal documents including text and statistical information graphics are suggested. One suggestion is that the position and the number of verbal annotations should be selected appropriately, another is that the graph line smoothing should be done cautiously.

Elderly Speech-Gaze Interaction

Elderly people face problems when using current forms of Human-Computer Interaction (HCI). Developing novel and natural methods of interaction would facilitate resolving some of those issues. We propose that HCI can be improved by combining communication modalities, in particular, speech and gaze, in various ways. This study presents elderly speech-gaze interaction as a novel method in HCI, a review of literature for its potential of use, and discusses possible domains of application for further empirical investigations.