Anthony F. Norcio

Mental models: concepts for human-computer interaction research

Abstract In interacting with the world, people form internal representations or mental models of themselves and the objects with which they interact (Norman, 1983a). According to Norman, mental models provide predictive and explanatory powers for understanding the interaction. More abstractly, Gentner and Stevens (1983) propose that mental models focus on the way people understand a specific knowledge domain. More concretely, Carroll (1984) views mental models as information that is input into cognitive structures and processes. What are mental models? Are they always formed? When formed, what are their characteristics? What are the functional consequences of having no model (if that is possible), an immature model, or a mature model? This paper intends to explore these questions.

Adaptive human-computer interfaces: a literature survey and perspective

The authors present a survey of recent research in adaptive interface computer software as well as a discussion of factors that require consideration in designing this software. An adaptive interface needs to include a knowledge base that encompasses four domains. These four domains are knowledge of the current user, knowledge of the interaction scheme, knowledge of the problem task, and knowledge of the underlying system. The authors review and discuss these knowledge bases along with the positive and negative aspects of adaptive interfaces. >

Cultural differences on attention and perceived usability: Investigating color combinations of animated graphics

This experimental study investigates the effects of animated graphic colors on attention and perceived usability of users from two cultural groups, American and Thai. The experiment employs a three-way split-plot design with one between-subjects factor and two repeated-measures factors. The between-subjects factor contains two cultural groups, American and Thai. The two repeated-measures variables are a banner background color factor with six levels and a banner font color factor with two levels. Participants search for target words from text on Web pages that contain three animated banner graphics. The findings lead to the conclusion that users across cultures tend to ignore animated banner graphics when they look for specific information on highly informative Web pages. This study also suggests influences of culture on overall performance, overall retention, and overall self-reports on usability, regardless of differences in banner color combinations. Moreover, cultural differences on the self-report of attention drawing are also revealed in each banner color usage, except yellow banners with white text. This study does not aim at exploring superiority of participants between cultures. Rather, it attempts to explore some possible cultural differences in interacting with a computer interface that could facilitate cognition and perception of users from different cultural groups.

A Comparative Study Between Tablet and Laptop PCs: User Satisfaction and Preferences

Despite their popularity, usability studies concerning Tablet PCs are lacking. This study aimed at determining user satisfaction and preference aspects of Tablet PCs in comparison to laptop PCs and pen-and-paper environments. Several common computer tasks were examined in an experimental environment on 34 college student participants. User satisfaction and preferences were measured by comprehensive questionnaires. An analysis of variance was used for the empirical comparisons. Participants did not have any difficulty in reading, direct manipulation, and form filling tasks. There was a perception of a high number of errors by the participants for the writing task in Tablet PCs. Overall, participants found the general computing capabilities and portability of Tablet PCs impressive. However, the majority did not prefer Tablet PCs to laptop PCs to meet their everyday computing needs. Results can help designers improve the overall usability of the Tablet PC and help its development as a major computing medium.

User preferences discovery using fuzzy models

User preferences discovery aims to learn the patterns of user preferences for various services or items such as movies. Preferences discovery is essential to the development of intelligent personalization applications. Based on decision and utility theories, traditional approaches to preferences discovery explicitly query users about the behavior of value function, or utility of every outcome with respect to each decision criterion. Consequently, these approaches are generally error-prone and labor intensive. Although implicit elicitation approaches have been proposed to address the above limitations, extent approaches largely ignore multi-valued nature of item features and uncertainty associated with item features and user preferences. To address uncertainty due to vagueness and imprecision, this research proposed a general framework for preferences discovery based on fuzzy set theories. In addition, new fuzzy models were created for preferences discovery and representation. Further, an algorithm was developed to predict user preferences with uncertainty, and visualization of item features, user feedback, and the discovered preferences helped improve the interpretation of the discovered knowledge. The results of the simulation evaluation using a benchmark movie dataset revealed that the proposed preference discovery method: (1) doubled the accuracy of preference discovery as compared to random prediction; and (2) outperformed conventional techniques in making movie recommendation. These findings suggest that fuzzy models are effective for preferences patterns discovery, and personalized recommendation application.

Design guidelines for effective recommender system interfaces based on a usability criteria conceptual model: results from a college student population

With the retail electronic commerce being a major global shopping phenomenon, retailers need to develop additional tools to improve their sales. One such tool is a recommender system through which the shopping page recommends products to the shoppers using their past Web shopping and product search behaviour. While recommender systems are common, few studies exist regarding their usability and user preferences. In this study, a structured survey concerning what recommender systems should contain and how this content should be presented was administered on 131 college-aged online shoppers. Results indicate participants prefer specific recommender content. Price, image and names of products are identified as essential information, while product promotions, customer ratings and feedback are identified as secondary types of information. Shoppers preferred short and relevant recommender information, with a maximum of three recommendations on one page. Future studies may explore differences in preference of recommender systems based on different product types.

Individualizing user interfaces: application of the Grade of Membership (GoM) model for development of fuzzy user classes

Abstract We introduce a bidirectional associative memory (BAM). The stable points of the memory are naturally interpreted as (non-sharp) concepts – the memory performs association of extents and intents of concepts. We show that this memory is stable and that the set of all stable points forms a complete lattice. We propose a learning algorithm and prove that it enables perfect learning provided the training set forms a consistent conceptual structure. Examples demonstrating the results are presented. Unlike in the case of other associative memories (M. Arbib (Ed.), The Handbook of Brain Theory and Neural Networks, MIT Press, London, 1995) the formal apparatus, architecture, dynamics and convergence proof etc. are based on algebraic structures of fuzzy logic in narrow sense.

Indentation, documentation and programmer comprehension

Recent investigations into the psychological factors underlying computer programming have focused on the effects of internal documentation and statement indentation on programmer performance [1, 5, 7]. Using memory recall approaches several studies have concentrated on the relationship between logic segments of a programs algorithm and the memory organization of the programmer. Since memory organization appears to be a functional psychological process, it seems reasonable to assume that indentation and documentation function as aids to comprehension rather than as organizers for memory [4]. The purpose of this study was to examine experimentally the relationship between documentation, indentation and the comprehension of computer programs.

Training Novice Users in Developing Strategies for Responding to Errors When Browsing the Web

Novice users frequently make errors when learning a new computer task and spend a large portion of their time trying to recover from errors. Three methods for helping novice users respond to errors have been presented in the literature: error management training, exploratory training, and conceptual models. In error management training, errors are presented as opportunities for learning, and users are instructed in strategies for coping with errors. In exploration, users are given an overview of their environment and are taught how to navigate through their task environment. Conceptual models are graphical or mathematical representations of a system that correspond closely to the real-world system. This experiment tested the effectiveness of these different approaches on training novice users to use the Internet. In this experiment, users received 3 hr of training on the World Wide Web and then were asked to perform a set of information retrieval tasks. Performance was measured in two ways: task performance and performance time. Participants who received exploratory training had significantly higher task performance. Participants who received exploration and conceptual models, both individually and together, were able to complete the tasks in less time. Error management had no significant effect on the performance of participants. In the task application of Web browsing, exploration seems to be the most appropriate training method for novice users.

Exploring language in software process elicitation: A grounded theory approach

This paper presents the results of exploratory research that investigated how people describe software processes in natural language. We conducted a small field study with four participants working at an IT Help Desk. We elicited and documented a trouble ticketing process using a template under conditions similar to that of many process improvement initiatives. This study included two treatments. In the first treatment, the process engineer elicited information and documented the process. In the second treatment, the participants used the template to document the process on their own. The resulting data, including the process representations, observation field notes, and interview transcripts, were analyzed using a grounded theory approach. The results suggest that there are distinct ways in which process users describe process. We construct a theory that posits that descriptions of process are dependent upon perspectives shaped by the elicitation and process context. Future research will focus on the evaluation of this theory relative to other elicitation approaches and contexts.