A correction to this paper has been published: https://doi.org/10.1007/s00521-021-05904-z

In this paper we attempt to measure the semantic distance between forum dialogues in five MOOCs of different subject matters (humanities, mathematics and computing). We examine if such distance can provide evidence of transferable linguistic features, suggesting transferability of forum classification models. For this purpose, we employed Latent Dirichlet Allocation in order to extract the main discussion topics for each MOOC and proceeded to a pairwise semantic comparison between them. We focused on three categories of forum topics, i.e., Content-Related, Logistics-Related and Social Building. In the Content-Related discussions, the study confirmed semantic distance between the humanities course and the other four, while the distances among the mathematics and computing courses were shorter than expected. On the other hand, Logistics-Related and Social Building topics contained a more transferable set of features. The approach that we followed provides insights that could help MOOC researchers interpret the transferable features of their available data to employ in their classification tasks.

Supervised classification models are commonly used for classifying discussions in a MOOC forum. In most cases these models require a tedious process for manual labeling the forum messages as training data. So, new methods are needed to reduce the human effort necessary for the preparation of such training datasets. In this study we follow an incremental approach in order to examine how soon after the beginning of a new course, we have collected enough data for training a supervised classification model. We show that by employing features that derive from a seeded topic modeling method, we achieve classifiers with reliable performance early enough in the course life, thus reducing significantly the human effort. The content of the MOOC platform is used to bias the topic extraction towards discussions related to (a) course content, (b) logistics, or (c) social interactions. Then, we develop a supervised model at the start of each week based on the topic features of all previous weeks and evaluate its performance in classifying the discussions for the rest of the course. Our approach was implemented in three different MOOCs of different subjects and different sizes. The findings reveal that supervised models are able to perform reliably quite early in a MOOC's life and retain a steady overall accuracy across the remaining weeks, without requiring to be trained with the entire forum dataset.

Graphical password composition is an important part of graphical user authentication which affects the strength of the chosen password. Considering that graphical authentication is associated with visual search, perception, and information retrieval, in this paper we report on an eye-tracking study (N = 109) that aimed to investigate the effects of users’ cognitive styles toward the strength of the created passwords and shed light into whether and how the visual strategy of the users during graphical password composition is associated with the passwords’ strength. For doing so, we adopted Witkin’s Field Dependence-Independence theory, which underpins individual differences in visual information and cognitive processing, as graphical password composition tasks are associated with visual search. The analysis revealed that users with different cognitive processing characteristics followed different patterns of visual behavior during password composition which affected the strength of the created passwords. The findings underpin the need of considering human-cognitive characteristics as a design factor in graphical password schemes. The paper concludes by discussing implications for improving recognition-based graphical passwords through adaptation and personalization techniques based on individual cognitive characteristics.

The objective of this course, is to introduce participants to location-based games and the challenges relating of designing such games for children. Key characteristics of this game genre are introduced first, followed by a design framework and a set of design guidelines. Examples of location-based games will be presented and typical design patterns as extracted from previous workshops will be discussed. Typical course participants include interaction designers, game designers and developers, practitioners and researchers interested in location-based games and mobile learning.

Nowadays, technological advances introduce new visualization and user interaction possibilities. Focusing on the user authentication domain, graphical passwords are considered a better fit for interaction environments which lack a physical keyboard. Nonetheless, the current graphical user authentication schemes are deployed in conventional layouts, which introduce security vulnerabilities associated with the strength of the user selected passwords. Aiming to investigate the effectiveness of advanced visualization layouts in selecting stronger passwords, this paper reports a between-subject study, comparing two different design layouts a two-dimensional and a three dimensional. Results provide evidence that advanced visualization techniques provide a more suitable framework for deploying graphical user authentication schemes and underpin the need for considering such techniques for providing assistive and/or adaptive mechanisms to users aiming to assist them to create stronger graphical passwords.

Visual attention, search, processing and comprehension are important cognitive tasks during a graphical password composition activity. Aiming to shed light on whether individual differences on visual behavior affect the strength of the created passwords, we conducted an eye-tracking study (N=36), and adopted an accredited cognitive style theory to interpret the results. The analysis revealed that users with different cognitive styles followed different patterns of visual behavior which affected the strength of the created passwords. Motivated, by the results of the first study, we introduced adaptive characteristics to the user authentication mechanism, aiming to assist specific cognitive style user groups to create more secure passwords, and conducted a second study with a new sample (N=40) to test the adaptive characteristics. Results strengthen our assumptions that adaptive mechanisms based on users' differences in cognitive and visual behavior uncover a new perspective for improving the password's strength within graphical user authentication realms.

In this paper, we introduce a two-step method for estimating the strength of user-created graphical passwords based on the eye-gaze behaviour during password composition. First, the individuals' gaze patterns, represented by the unique fixations on each area of interest (AOI) and the total fixation duration per AOI, are calculated. Second, the gaze-based entropy of the individual is calculated. To investigate whether the proposed metric is a credible predictor of the password strength, we conducted two feasibility studies. Results revealed a strong positive correlation between the strength of the created passwords and the gaze-based entropy. Hence, we argue that the proposed gaze-based metric allows for unobtrusive prediction of the strength of the password a user is going to create and enables intervention to the password composition for helping users create stronger passwords.

Evidence suggests that individual cognitive differences affect users' memorability, visual behavior, and graphical passwords' security. Such knowledge denotes the added value of personalizing graphical password schemes towards the unique cognitive characteristics of the users. However, real-time and accurate cognition-based predictive user models are necessary to reach such a breakthrough. In this paper, we present the results of such an attempt, where an in-lab eye-tracking study was conducted with 36 participants who completed a recall-based graphical password composition task. We adopted a credible cognitive style theory, and investigated a variety of eye-tracking metrics to predict participants' cognitive styles. Results' analysis reveals that inferring individual cognitive differences in real-time during graphical password composition is feasible within a few seconds and that specific eye-tracking metrics correlate stronger with certain cognitive style groups. The findings further support the vision of incorporating real-time adaptive mechanisms in graphical password schemes for the benefit of service providers and end-users.

This paper discusses our experience with designing and implementing a new Introduction to Computing course that aims both to introduce students to programming and at the same time to cover key concepts of Computer Science using a hands-on experiential approach. The re-design of the course has put more emphasis on using Python as a tool for studying computer science. It was found that the students enjoyed this approach and responded positively to the challenge. Examples are given on how concepts of binary arithmetic, computer architecture, operating systems, networking have been introduced through Python coding examples and exercises, while the project work introduced the students to the challenges of software development.

Recent research provides evidence that individual differences in human cognitive styles affect user performance and experience in diverse application domains. However, state-of-the-art elicitation methods of cognitive styles require researchers to apply explicit, in-lab, and time-consuming "paper-and-pencil" techniques, rendering real-time integration of cognitive styles? elicitation impractical in interactive system design. Aiming to elaborate an implicit elicitation method of cognitive styles, this paper reports two feasibility studies based on an eye-tracking multifactorial model. In both studies, participants performed visual activities of varying characteristics, and the eye-tracking analysis revealed quantitative differences on visual behavior among individuals with different cognitive styles. Based on these differences, a series of classification experiments were conducted, and the results revealed that gaze-based implicit elicitation of cognitive styles in real-time is feasible, which could be used by interactive systems to adapt to the users' cognitive needs and preferences, to better assist them, and improve their performance and experience.

This paper investigates the trade-off between security and usability in recognition-based graphical authentication mechanisms. Through a user study (N=103) based on a real usage scenario, it draws insights about the security strength and memorability of a chosen password with respect to the amount of images presented to users during sign-up. In particular, it reveals the users' predisposition in following predictable patterns when selecting graphical passwords, and its effect on practical security strength. It also demonstrates that a "sweet-spot" exists between security and usability in graphical authentication approaches on the basis of adjusting accordingly the image grid size presented to users when creating passwords. The results of the study can be leveraged by researchers and practitioners engaged in designing intelligent graphical authentication user interfaces for striking an appropriate balance between security and usability.

This paper reports the results of a study of software development organizations' approach towards usability, conducted on software development organizations in Greece, extending a survey conducted in Southern Italy in 2011. The results show that the organization performing usability evaluation is nearly the same in both countries as well as the key advantages and the problems in performing usability evaluation emphasized by Italian and Greek respondents. A difference in the understanding of usability evaluation concept between the two studies emerged.

In this paper, we propose a method for the real time evaluation of collaborative activities. The method aims to classify collaborative activities using a memory-based learning model and to evaluate them using a reference set of pre-evaluated activities. The proposed approach uses time series to represent activities and classifies them regarding their similarity. In order to evaluate the results, the method is used as an automatic rater of collaboration quality and the ratings are compared to ratings of human experts.

When people interact with digital artefacts they perceive their pragmatic and hedonic qualities. In the case of interacting with mobile devices and applications, users seek utility as they try to satisfy certain needs, but at the same time they have certain feelings and emotions when, for example, they feel attached to their personal phone and/or trust its brand. Due to this strong relation between users and mobile devices a significant problem occurs when researchers want to evaluate the user experience of a mobile application in laboratory settings: the selection of an appropriate mobile device. Towards this end, this paper aims to unveil the effect of perceived hedonic quality of a mobile device on the user experience evaluation results of an application. Our results show that the perceived hedonic quality of a mobile device significantly affected the perceived pragmatic quality of the application, but not the hedonic one.

This article presents the results of a design workshop that developed scenarios of learning in an imaginary "smart city": Villard-de-Lans (Vercors, French Alps) by exploring suitable methodological approaches to the Smart City Learning Design. The aim of this case study was to propose "glocal" solutions intended to balance the global trends and the expectations of the community of reference (local elements), while distinguishing between access to information and participation in informal learning processes located in a smart city.

A "Completely Automated Public Turing test to tell Computers and Humans Apart" (CAPTCHA) is a mechanism widely used nowadays for protection of web applications, interfaces, and services from malicious users. A questionnaire-based survey combined with a real usage scenario of a native-language CAPTCHA mechanism was conducted in order to investigate several aspects that affect end-user perceptions related to the quality of CAPTCHA. A total of 210 participants of age between 19 and 64 participated during May and July 2010. The survey results validate the common belief that CAPTCHAs are still difficult for humans to solve. They also provide insights that can be applied to improve users' experience on interacting with CAPTCHA systems.

Multi-user virtual environments (MUVEs) seem to have great potential in education. Current educational uses of MUVEs seem to exploit them more as group interaction platforms and less as worlds where users learn by interacting and modifying the environment in a constructivist approach. There is also a need for systematic research efforts that will lead to guidelines and principles for designing and evaluating effective learning activities in MUVEs. This paper presents preliminary empirical results from an exploratory study with university students. A collaborative problem-based physics learning activity was designed in Second Life® (SL), following a constructivist approach. Students (n=30) collaborated “in-world” in pairs assisted by a tutor, in order to solve the problem. Data were gathered using a questionnaire and session recordings. The study focused on issues related to educational environment design, collaboration and instruction. Results indicate that satisfactory, engaging and effective collaborative learning activities can be realized in SL.

In this paper, we describe two educational games mediated by mobile technology which were designed for use in the context of a traditional historical museum by young children. Our analysis focuses on the principles of the educational design, on the use of mobile technology and on the envisaged interaction between the exhibits and the children. The main argument of the paper is that mobile technology can support the play with the exhibits of a museum -instead of just viewing them in the more traditional way--and in this context the spectrum of children interaction with the exhibits can be broadened and enriched.

In this paper, we describe an innovative tool that supports the design and evaluation of the information architecture of a Web site. The tool uses Latent Semantic Analysis and hierarchical clustering algorithms to provide optimal information navigation schemes in an automated manner. The proposed, tool-based, approach addresses the problem of reasonable content structuring, which established techniques such as card sorting also address. A real world case study depicted substantial effectiveness gain, without expense in the quality of results. We argue that such an approach could facilitate information-rich applications design, like most Web sites, by reducing time and resources required.

Structuring of the content is an important step in web site design, affecting greatly navigability and the overall user experience. Automated support of this task is the object of this paper. AutoCardSorter, a computational tool that supports clustering of the web pages of a site, is introduced. The proposed tool-based methodology uses semantic similarity measures, such as latent semantic analysis, and hierarchical clustering algorithms, in order to suggest suitable information navigation schemes. In the paper, after introducing AutoCardSorter design and functionality, three independent studies are discussed. The studies, that were conducted in order to validate the proposal, compared the proposed method with the established card-sorting approach, in different domains. It was found that substantial gain in effectiveness was achieved without expense in the quality of results, therefore, reducing the required time and human resources.

Computer supported collaborative learning activities involve combination of complex software tools that often need to interoperate in a wider context of learning. This paper proposes a data model that accommodates requirements of typical collaborative learning situations and facilitates interoperability of tools and interchange of products of collaboration and evaluation data. The model has been tested against various typical tools used for both synchronous and asynchronous collaboration of groups of students

Observation and understanding of real world activities and phenomena is a basis of inquiry and reasoning and subsequently building of scientific knowledge. This involves moving from the perception of real world phenomena to constructing and exploring qualitative and quantitative relations that hold among the main elements. The transition between the two phases is not always smooth for the learners involved. In this paper, we present tools and activities that attempt to bridge the gap between the physical world experience and the abstract modeling and reasoning phase. Firstly, we discuss a modeling approach and the various representations involved. Then, we present the Video2Frames tool of ModellingSpace which is proposed to be used in order to create educational material by allowing the creation of abstract entities from video recordings of phenomena. Next an example of creation of educational material, using this approach is presented and discussed.

In this paper, we describe the experience of designing a collaborative learning activity for a traditional historical/cultural museum. The activity, based on a Mystery in the Museum story, involves collaboration of small groups of students through mobile handheld devices. An application has been built that permits authoring of such activities, while a usability evaluation study was performed that revealed some of the limitations of the design. The reported findings can be of use to those interested in following similar approaches in cultural and educational settings, and draw conclusions of general interest relating to interaction and collaboration through mobile technology.

The growth of mobile technology has made recording of user's location possible. The systems that intent to use location in order to register user's movement and to use the generated data for extracting useful knowledge define a new area of research that has technological as well as theoretical underpinnings. Many location based systems have been developed until now and some first directions and experiences have emerged. In this paper we focus on how some representative examples of these systems collect location information, what parameters use for tracking location and motion, how they model location, and thus tendencies appear on locating persons and objects.

This paper includes a review of mobile applications used in museum environments, focusing on the notion of context and its constituent dimensions. Museums are a representative example in which the context influences interaction. During a museum visit, the visitors interact with the exhibits through mobile devices. We argue that, effective interaction design needs to take into consideration multiple dimensions of the context. Since context is often misinterpreted, superficially used or poorly defined, we attempt to analyze a number of existing mobile applications used in museum environments, through this perspective. The point of analysis is to evaluate those applications against various context dimensions. We argue that these results can be useful in other kinds of applications, in which the impact of context is not taken for granted.

This paper presents Synergo, a new collaboration support environment that monitors the activity and permits visualization of various quantitative parameters, like density of interaction, symmetry of the activity, degree of collaboration etc, particularly useful for understanding the mechanics of collaboration. Synergo has been proposed as a testbed for analysis of small-group model-building synchronous interaction. 1.

This paper describes our experience with introduction of synchronous collaborative problem solving activities in the frame of a distance learning computer science undergraduate course of the Hellenic Open University (HOU). Groups of students worked collaboratively at a distance in order to build a flowchart of an algorithm to a given problem. The technological and organization issues involved, the first findings of analysis of peer student interaction during this study, as well as some general implications for distance education are discussed.

Analysis of collaborative problem solving involves analysis of dialogue and interaction, analysis of tasks and social roles through ethnographic and other field studies. Use of tools to facilitate this process can be very useful. We discuss first the key requirements of a new generation of interaction and collaboration analysis tools. We then present how these requirements have lead to the design of prototype tools, recently developed. These tools can relate and synchronize various streams of field data. An important characteristic of the tools is their support for a multilayer structure of annotations of various levels of abstraction, through which the activity can be interpreted and presented.

It is believed that computer-supported collaboration at a distance can stimulate learning. An innovative environment that permits real-time collaborative problem solving is described. In particular we study the effect of two alternative coordination mechanisms on the problem solving activity of pairs of students engaged in concept map building. The first mechanism imposes locking of the shared activity board for one student at a time, while the second mechanism allows access of all group members to the shared activity board in a contemporary way. The reported findings are of interest to researchers and practitioners who are involved in the design and study of real-time collaborative learning environments.

As knowledge-based techniques are introduced in supervision and control applications, the need for a structured, methodological approach in the development of these systems increases. Current knowledge-based systems development methodologies are founded on individualistic models of expertise, and cannot face the challenge of interacting with humans or other systems in dynamic application environments. This article introduces a development method that combines models of expertise with interaction-based distributed artificial intelligence. The applicability of the method is demonstrated on an example of supervision of a power transmission network. The analysis of the proposed system is based on the KADS methodology. The design phase is structured in a series of steps: first, the domain description is used to select a model of distributed problem solving. Then, problem constraints and a set of design rules guide the mapping of the analysis' entities to a design solution. Design decisions are justified at every step. Alternative design proposals are experimentally compared with the aid of a multi-agent platform and a simulator. The experimental results indicate possible design refinements. Finally, the generality of the approach is discussed and future research directions are indicated.>