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Contribution: This research illuminates information entropy's efficacy as a pivotal educational tool in programming, enabling the precise quantification of algorithmic complexity and student abstraction levels for solving problems. This approach can provide students quantitative, comparative insights into the differences between optimal and student implemented solution, and allowing educators to offer targeted feedback, thereby optimizing the learning and abstraction processes in algorithm design through deliberate practice. Background: Abstraction is considered one of the most important skills in problem solving. Many studies in programming have shown that higher abstraction capability can significantly simplify problems, reduce program complexity and improve efficiency. However, it is difficult to develop criteria to measure the level of abstraction, and there is still a lack of relevant systematic research. Research Questions: 1) How can students' abstraction ability in programming be effectively measured? and 2) How to develop programming education and training methods based on the measurement of abstraction ability? Methodology: Forty-six grade 10 students participated in the experiment, divided into two groups for programming training using information-entropy-based assessment and traditional learning methods. Their level of computational thinking, algorithmic efficiency improvements, and test scores were used to measure performance and to analyze the effectiveness of the training methods. Findings: Through empirical research, this article finds that information-entropy-based assessment can reflect the differences in problem solving among students possessing varying capabilities. Information entropy can be crucial for evaluating and improving students' abstraction performance and algorithm efficiency.

Online discussion research has mainly been conducted using case methods. This article proposes a method for comparative analysis based on network metrics such as information entropy and global network efficiency as more holistic measures characterizing social learning group dynamics. We applied social learning optimization analysis of networks (SLOAN) to a data set consisting of Coursera courses from a range of disciplines. We examined the relationship of discussion forum uses and measures of network efficiency, characterized by the information flow through the network. Discussion forums vary greatly in size and in use. Courses with a greater prevalence of subject-related versus procedural talk differed significantly in seeking but not disseminating behaviors in massive open online course discussion forums. Subject-related talk was related to higher network efficiency and had higher seeking and disseminating scores overall. We discuss the value of SLOAN for social learning and argue for the experimental study of online discussion optimization using a discussion post recommendation system for maximizing social learning.

In this paper, we demonstrate how to identify whether different groups of students (classified by their major) provide different quantities of information in their student ratings of instruction (SROIs). As a corollary, we identified specific groups of students who provided a greater/lesser quantity of information in their responses. All calculations were undertaken using Microsoft Excel, and no prior statistical training was required to create or interpret our information measures. We used SROI data taken from a first-year logical reasoning course for health professions majors and found that the quantity of information provided by pharmacy and other health majors in their SROIs exceeded the quantity of information provided by nursing majors for every single SROI question. We also found that specific majors gave relatively greater quantities of information (relative to other majors) for specific types of SROI items.

A study of online search, especially search performance, is vital because people heavily rely on the Internet nowadays. The purposes of this study are thus to examine the gratification needs affecting Internet users' intention to search information online, to explore the antecedents of online search performance, and to investigate online information-seeking behavior according to each search purpose. A survey of Internet users in Thailand is carried out. Data are collected extensively both from students and workers. Four hundred fifty-three questionnaires are collected online. Individuals use the Internet to search for information differently, for academic/ working achievement, problem-solving, and personal information needs. The main gratifications are information seeking and Internet ambiance. Internet search intention is a strong determinant of a user's online search performance and corresponding behavior. The theoretical implication is that researchers could apply the research framework to other contexts such as the specific information search. Information source providers could use the findings to modify online resources and their presentations for users effectively. Teachers/ managers could guide their students/ workers to search effectively. This study combines the U&G and the TPB theories. The novel aspects of gratifications i.e., antitraditional media sentiment and Internet ambiance are also explored.

Labeling information is a precarious and risky enterprise. Catalogers have the task of fitting unique concepts within established and rigid language frameworks while also minimizing personal bias. The way information literacy librarians interact with labeled information also influences how users interact with information. Labeling moves beyond the role of categorizing; it also contributes to meaning making and knowledge building. Wittgenstein's "Philosophical Investigations" serves as a philosophical footing to illustrate how the labeling of things, in this case information, shapes the way we give things meaning. Critical librarianship and philosophy of information theory add to the discussion by considering how personal perspective, power, and bias to manipulate the game of naming information that takes place in the information literacy classroom. This paper is an invitation for librarians to reflect upon the relationship between labeling and how all users of information engage with labels and subsequently create meaning and knowledge.

While limited research on the information behaviors of community college students exists, the theories of Elfreda Chatman have not been used to develop understanding of this population. Community college students are more likely to be people of color and/or lower income than their peers in four-year colleges, making them potentially more likely to experience information poverty. This study explored if and how Chatman's theories explain the information behaviors of students at a highly diverse, urban community college. Thirteen students were interviewed using open-ended, qualitative prompts to describe their information seeking and use as it pertains to their college experiences, specifically advisement, financial aid, and understanding course requirements. Students indicated that they used interpersonal and online resources in some combination for all of their information needs for school and in everyday life. The students did not describe the information poverty theorized in many of Chatman's studies. However, it became clear from their responses that the students' information seeking and use, as well as their understanding of their own information behaviors, support a view of the community college as a small world that privileges information seeking as a normative behavior.

Communication theory can be challenging to teach in an engaging manner. The following original teaching activity suggests a way to incorporate the phenomenon of escape rooms into your theory classroom. Courses: Communication Theory, Introduction to Communication. Objectives: In this activity, students will apply the basic tenets of several communication theories--emotional contagion, cultivation theory, exemplification theory, and politeness theory--in solving a puzzle. Students will also apply theory by examining their own group processes during the activity through the lens of the functional perspective on group decision making.

This article reports on an experience where arts-informed pedagogy was combined with the traditional lecture-style teaching in a course on information and communication theories delivered at the Masters level in the School of Journalism and Communication Sciences (EJCAM) at Aix-Marseille University in France. After the course content had been delivered orally, students were required to work in groups to create art exhibits that showcased how information and communication theories operated in different historical or contemporary situations in the society. Sixteen impressive art projects were created by the students, and an arts exhibition was held within the school premises. To gauge students' reception of how the arts-informed pedagogy contributed to their appropriation of the course content, they completed an online survey two months after the course. Their responses showed an overwhelmingly positive reception and demand for more creative modes of learning in information and communication studies. The arts approach complemented the verbal mode of learning by creating a recursive and collaborative learning environment that enhanced students' participation, self-esteem, and creativity and served to illustrate the interdependence between theory and practice.

The study of communication through the framework of established theories is central to communication education, and most undergraduate communication programs include a course dedicated to surveying theoretical perspectives. This activity guides students to review and synthesize theoretical knowledge in a March Madness-style end-of-semester competition. The purpose is threefold. First, students revisit theories covered over the semester, providing a valuable review opportunity. Second, students gain experience evaluating strengths and weaknesses of individual theories in comparison with others. Third, by considering theories in competition, students engage with broader metatheoretical questions in the study of communication. Courses: Communication Theory, Advanced Interpersonal Communication, Organizational Communication Theory. Objectives: The purpose of this end-of-semester activity is to demonstrate (1) students' ability to compare and contrast communication theories, (2) students' competency in evaluating communication theories, and (3) students' proficiency in discussing broader theoretical issues in the study of communication.

The measurement of knowledge contribution in collaborative knowledge building is an important research topic in computer-supported collaborative learning. The information measures of knowledge contribution based on information theory are proposed in this study, which includes two measures: amount of information and information gain. Discourse data collected from a collaborative knowledge building activity were analyzed to validate these measures. The results showed that our information measures can complement the traditional behavioral. With the help of the two measures, community-level variation tendency and individual-level knowledge contribution characteristics could be analyzed in collaborative knowledge building activities. A log function was used to fit the community knowledge variation tendency to measure the convergence of knowledge building. Students were clustered into five types according to their behaviors and contributions in collaborative knowledge building. Both teachers and researchers can benefit from these two information measures by using them in practice.

How do children learn to communicate, and what do they learn? Traditionally, most theories have taken an associative, compositional approach to these questions, supposing children acquire an inventory of form-meaning associations, and procedures for composing / decomposing them; into / from messages in production and comprehension. This paper presents an alternative account of human communication and its acquisition based on the systematic, discriminative approach embodied in psychological and computational models of learning, and formally described by communication theory. It describes how discriminative learning theory offers an alternative perspective on the way that systems of semantic cues are conditioned onto communicative codes, while information theory provides a very different view of the nature of the codes themselves. It shows how the distributional properties of languages satisfy the communicative requirements described in information theory, enabling language learners to align their expectations despite the vastly different levels of experience among language users, and to master communication systems far more abstract than linguistic intuitions traditionally assume. Topics reviewed include morphological development, the acquisition of verb argument structures, and the functions of linguistic systems that have proven to be stumbling blocks for compositional theories: grammatical gender and personal names.

Students across disciplines struggle with sensemaking when they are faced with the need to understand and analyze massive amounts of information. This is particularly salient in the disciplines of both history and data science. Our approach to helping students build expertise with complex information leverages activity theory to think about the design of a classroom activity system integrated with the design of a collaborative open-source network-analysis software tool called Net.Create. Through analysis of network log data as well as video data of students' collaborative interactions with Net.Create, we explore how our activity system helped students reconcile common contradictions that create barriers to dealing with complex datasets in large lecture classrooms. Findings show that as students draw on details in a historical text to collaboratively construct a larger network, they begin to move more readily between small detail and aggregate overview. Students at both high and low initial skill levels were able to increase the complexity of their historical analyses through their engagement with the Net.Create tool and activities. Net.Create transforms the limitation of large class sizes in history classrooms into a resource for students' collaborative knowledge building, and through collaborative data entry it supports the historiographic practices of citation and revision and helps students embed local historical actors into a larger historical context.

Introduction: This paper elaborates the picture of information sharing and knowledge sharing as forms of communicative activity. Method: A conceptual analysis was made to find out how researchers have approached information sharing and knowledge sharing from the perspectives of transmission and ritual. The findings are based on the analysis of one hundred and two key studies characterising the above viewpoints. Results: Information sharing and knowledge sharing represent similar communicative activities when looked at from the viewpoints of transmission and ritual communities. The former view emphasises one-way communication from sender to recipients, and the sharing activity appears as transfer, diffusion or provision of information or knowledge. From the ritual point of view, the sharing activity has been conceptualised in terms of exchange depicting two-way communication between interacting participants. The activities of knowledge sharing have mainly been examined in work-related contexts, while information sharing has also been investigated in non-work contexts. Conclusions: As communicative activities, information sharing and knowledge sharing have more similarities than differences. However, the terminological questions become more complicated if the focus is shifted to what exactly is being shared while sharing information or knowledge, due to multiple interpretations of the concepts of information and knowledge.

This teaching activity explores whether the meaningful communication case for diversity in groups, organizations, and communities rests in ideas of justice, equity, and basic employee responsibilities and rights (O'Leary & Weathington, 2006. Beyond the Business Case for Diversity in Organizations. Employee Responsibilities and Rights Journal, 18(4), 283-292. https://doi.org/10.1007/s10672-006-9024-9) rather than in the business case. This article responds to neoliberal multiculturalism to articulate how a justice case for diversity might instead be presented in the classroom. The justice case may provide a more robust orientation to diverse communicators in future small group, organizational, and community contexts. Courses: Communication Theory, Organizational Communication, Small Group Communication. Objectives: This activity introduces students to two major rationales for organizational diversity--the business case and the social justice case--and allows exploration of how attitudes toward diversity might be affected by challenges presented in diverse organizations. The debriefing discussion encouraged students to explore the arguments for diversity presented by each case and the resilience of pro-diversity arguments in light of possible challenges. This activity can also be used as a prompt for students to reflect on the arguments for diversity presented across the curriculum.

Often, users of information systems (both automated and manual) must analyze those systems in a "black box" fashion, without being able to see the internals of how the system is supposed to work. In this case of business process outsourcing, an insurance industry customer encounters an ongoing stream of customer service issues, with both the original provider and outsourcing organization. To understand and validate what is happening with his account, the insurance customer (Edward) and his representative (Penny) must deduce the operations, business rules, and data flows of the organizations. Most importantly, have the operations of these organizations released anyone's data inappropriately? And are these same customer service issues happening to other customers, who may not be in a position to spend the time and energy needed to catch and resolve them?

Monitoring and control over the process of studying the distance learning course are based on solving the problem of making out an adequate integral mark to the educatee for mastering entire study course, by testing results. It is suggested to use the degree of correspondence between educatee's thesaurus and the study course thesaurus as an integral mark for the degree of mastering the distance learning course. Study course thesaurus is a set of the course objects with relations between them specified. The article considers metrics of the study course thesaurus complexity, made on the basis of the graph theory and the information theory. It is suggested to use the amount of information contained in the study course thesaurus graph as the metrics of the study course thesaurus complexity. Educatee's thesaurus is considered as an object of measuring educational material learned at the semantic level and is assessed on the basis of amount of information contained in its graph, taking into account the factors of learning the thesaurus objects.

The acceptability of sentences in natural language is constrained not only grammaticality, but also by the relationship between what is being conveyed and such factors as context and the beliefs of interlocutors. In many languages the critical element in a sentence (its focus) must be given grammatical prominence. There are different accounts of the nature of focus marking. Some researchers treat it as the grammatical realization of a potentially arbitrary feature of universal grammar and do not provide an explicit account of its origins; others have argued, however, that focus marking is a (grammaticalized) functional solution to the problem of efficiently transmitting information via a noisy channel. By adding redundancy to highlight critical elements in particular, focus protects key parts of the message from noise. If this information-theoretic account is true, then we should expect focus-like behavior to emerge even in non-linguistic communication systems given sufficient noise and pressures for efficiency. We tested this in an experiment in which participants played a simple communication game in which they had to click cells on a grid to communicate one of two line figures drawn across the grid. We manipulated the noise, available time, and required effort, and measured patterns of redundancy. Because the lines in many cases overlapped, meaning that only some parts of each line could be used to distinguish it from the other, we were able to compare the extent to which effort was expended on adding redundancy to critical (non-overlapping) and non-critical (overlapping) parts of the message. The results supported the information-theoretic account of focus and shed light on the emergence of information structure in language.

Introduction: Rolf Landauer declared in 1991 that "information is physical". Since then, information has come to be seen by many physicists as a fundamental component of the physical world; indeed by some as the physical component. This idea is now gaining currency in popular science communication. However, it is often far from clear what exactly this statement means; exactly how is information physical? And why this should matter for information science? The purpose of this paper is to clarify just what is meant by the physical nature of information, and the significance of these considerations for our discipline. Methods: A selective literature review and conceptual analysis, based on literature from both physical science and information science. Results: The prospect of attempting to make links between objective and subjective conceptions of information has been strongly advocated by some authors and doubted by others. The physical nature of information can be understood from three main perspectives: the relation between information and physical entropy; the strongly informational nature of the quantum view of nature; and the possibility of recasting physical laws in informational terms. Conclusions: Based on this analysis, we muse on the relevance of such issues to information science, with particular reference to emergent properties of information. Apart from the added public awareness of the i-word in a very different context from the norm, it may that that there are general laws and principles, or at least useful metaphors and analogies, linking the concept of information in the physical, biological and social domains. [This paper was published as part of: Proceedings of the Eighth International Conference on Conceptions of Library and Information Science, Copenhagen, Denmark, 19-22 August, 2013.]

Digital educational games (DEGs) possess the potential of providing an appealing and intrinsically motivating learning context. Usually this potential is either taken for granted or examined through questionnaires or interviews in the course of evaluation studies. However, an "adaptive" game would increase the probability of a DEG being actually motivating and emotionally appealing. In order to adapt the game to the learner's motivational and emotional state "while" engaged with a particular game scenario, an ongoing assessment of these states is required. An explicit assessment, e.g. by questionnaires occurring repeatedly in short time intervals on the screen would probably destroy the learner's flow experience. Thus, it is necessary to apply an approach that assesses the learner's current states in a non-invasive way. In the course of this paper we describe such a non-invasive, implicit assessment procedure which is based on the interpretation of "behavioral indicators". A set of behavioral indicators has been elaborated whereby some of them are derived from the theory of "information foraging" (Pirolli and Card, 1999). Values for each behavioral indicator (e.g. amount, frequency, seconds, etc.) are gathered after equally long lasting "time slices". After each time slice, these values serve as weighted predictors to multiple regression equations for the dimensions of a motivation model, an emotion model and a construct called clearness. The motivation model is based on the two dimensions of "approach" and "avoidance motivation". The emotion model encompasses the dimensions "valence" and "activation". Clearness is defined as appropriate problem representation. A comparison of the resulting values on these dimensions between the current and previous time slices cove rs fluctuations of the learner's states over time. The assessment of such changes forms the prerequisite for providing in-game adaptations which aim to enhance the learner's state, targeting towards a full exploitation of DEGs' pedagogical potential. (Contains 2 tables and 2 figures.)

Introduction: The study contributes to the conceptual investigation of information use by reviewing the conceptions of epistemic work proposed by Cook and Brown, and knowing in practice proposed by Orlikowski. The above conceptions are developed in the field of organization science. Method: The key articles by Cook and Brown, and Orlikowski were scrutinized by means of in-depth conceptual analysis. The main focus was placed on the comparative analysis of the conceptions of epistemic work and knowing in practice. Results: The approach to epistemic work conceptualizes information use as the employment of tacit and explicit knowledge in the service of knowing. Knowing is understood as epistemic work that is done as an inherent part of action. Orlikowski approaches information use as construction and reconstruction of knowledgeability in and through action. Conclusions: The conceptions of epistemic work and knowing in practice provide holistic frameworks for the study of information use in context, while not probing the details of information use processes per se. (Contains 1 table.)

Searching for information is critical in many situations. In medicine, for instance, careful choice of a diagnostic test can help narrow down the range of plausible diseases that the patient might have. In a probabilistic framework, test selection is often modeled by assuming that people's goal is to reduce uncertainty about possible states of the world. In cognitive science, psychology, and medical decision making, Shannon entropy is the most prominent and most widely used model to formalize probabilistic uncertainty and the reduction thereof. However, a variety of alternative entropy metrics (Hartley, Quadratic, Tsallis, Rényi, and more) are popular in the social and the natural sciences, computer science, and philosophy of science. Particular entropy measures have been predominant in particular research areas, and it is often an open issue whether these divergences emerge from different theoretical and practical goals or are merely due to historical accident. Cutting across disciplinary boundaries, we show that several entropy and entropy reduction measures arise as special cases in a unified formalism, the Sharma-Mittal framework. Using mathematical results, computer simulations, and analyses of published behavioral data, we discuss four key questions: How do various entropy models relate to each other? What insights can be obtained by considering diverse entropy models within a unified framework? What is the psychological plausibility of different entropy models? What new questions and insights for research on human information acquisition follow? Our work provides several new pathways for theoretical and empirical research, reconciling apparently conflicting approaches and empirical findings within a comprehensive and unified information-theoretic formalism.

This paper reports on an experiment of using a hybrid pedagogical approach to tackle the challenge of teaching "Information and Communication theories" to students enrolled in Master of Communication and Digital Content at the School of Communication and Journalism of Aix Marseille University in France. The hybrid pedagogical approach combines the classical textual/verbal approach with an arts informed pedagogy, augmented by creative writing and storytelling activities. The fact that the arts-informed approach was not used in isolation but in combination with the traditional textual/verbal approach and creative writing and storytelling activities offered students a wide choice of learning modalities through which they could express themselves. Our preliminary findings suggest that using a hybrid pedagogical approach rather than one single pedagogical approach improved students' understanding of the abstract concepts implied by the communication theories discussed during the lectures. Students illustrated their understanding of these theories by recasting them in various real life or plausible situations during the creative writing activity which we call "Communication Stories" or cStories.

Given a system of multiple random variables, a new measure called the "L"-multivariate association coefficient is defined using (conditional) entropy. Unlike traditional correlation measures, the L-multivariate association coefficient measures the multiassociations or multirelations among the multiple variables in the given system; that is, the "L"-multivariate association coefficient measures the degree of the association for the given system. The "L"-multivariate association coefficient for the system of two random variables is also called the "L"-bivariate association coefficient. The association measured by the "L"-multivariate association coefficient is a general type of association, not any specific type of a linear or nonlinear association. Unlike the K-dependence coefficient, which is an asymmetrical measure, the "L"-multivariate association coefficient is a symmetrical measure. A direct application of the "L"-multivariate association coefficient is in variables selection or variables reduction. This paper also explores the relationship between the "L"-multivariate association coefficient and the "K"-dependence coefficient.

In multivariate statistics, the linear relationship among random variables has been fully explored in the past. This paper looks into the dependence of one group of random variables on another group of random variables using (conditional) entropy. A new measure, called the K-dependence coefficient or dependence coefficient, is defined using (conditional) entropy. This paper shows that the K-dependence coefficient is a measure of the degree of dependence of one group of random variables on another group of random variables. The dependence measured by the K-dependence coefficient includes both linear and nonlinear dependencies between two groups of random variables. Therefore, the K-dependence coefficient measures the total degree of dependence and not just the linear component of the dependence between the two groups of random variables. Furthermore, the concept of the K-dependence coefficient is extended by defining the partial K-dependence coefficient and the semipartial K-dependence coefficient. Properties of partial and semipartial K-dependence coefficients are also explored.

In item-response theory, if a latent-structure model has an ability variable, then elementary information theory may be employed to provide a criterion for evaluation of the information the test provides concerning ability. This criterion may be considered even in cases in which the latent-structure model is not valid, although interpretation of the criterion is more complex in this case. It is also possible to consider reliability results for inferences about the ability variable. Use of sampling to develop required parameter estimates is straightforward. Applications of the criterion in zero-, one-, and two-parameter logistic (0PL, 1PL, and 2PL) examples are provided.

This paper provides an example of how institutional service-learning assessment data can be used to drive organizational change. Furco's (1999) self-assessment rubric for the institutionalization of service-learning in higher education is used in modified form as the instrument through which organizational-level assessments were made. The process of organizational change over time is reported through the lens of Weick's (1995) Organizational Information Theory and specifically the double interact, comprised of act, response, and adjustment as organizational members reduce their uncertainty and make sense of organizational action and communication. (Contains 1 table and 1 note.)

Introduction: The article argues for a closer association between information seeking research and the practices of teaching information seeking. Findings are presented from a research project on information seeking, didactics and learning (IDOL) investigating librarians' and teachers' experiences of teaching information seeking. Method: Thirteen teachers and five librarians, teaching 12-19 year-old students in three schools, participated. Forty-five interviews were conducted over a period of three years. Analysis: The IDOL project adopted a phenomenographic approach with the purpose of describing patterns of variation in experiences. The findings were also analysed by way of relating them to four competing approaches to the mediation of information literacy. Results: A gap was identified between experiences of teaching content that focused on sources and order, and experiences of assessment criteria applied to students' work that focused on the importance of correct facts and the analysis of information. These findings indicate a highly restricted range of teaching contents when compared with the four theoretical approaches to the mediation of information literacy. Conclusion: Teaching information seeking might be enhanced by a wider repertoire of contents reflecting more varied theoretical understandings developed in information seeking research, particularly as regards the importance of content and context related to user perspectives.

The rise of learning analytics, the application of complex metrics developed to exploit the proliferation of "Big Data" in educational work, raises important moral questions about the nature of what is measurable in education. Teachers, schools and nations are increasingly held to account based on metrics, exacerbating the tendency for fine-grained measurement of learning experiences. In this article, the origins of learning analytics ontology are explored, drawing upon core ideas in the philosophy of computing, such as the general definition of information and the information-theoretic account of knowledge. Drawing upon a reading of Descartes "Meditatio II," which extends the phenomenology of Jean-Luc Marion into a pedagogy of intentionality, the article identifies a fundamental incompatibility between the subjective experience of learning and the information-theoretic account of knowledge. Human subjects experience and value their own information incommensurably with the ways in which computers measure and quantify information. The consequences of this finding for the design of online learning environments, and the necessary limitations of learning analytics and measurement are explored.

Interactive learning tools are emerging as effective educational materials in the area of computer science and engineering. It is a research domain that is rapidly expanding because of its positive impacts on motivating and improving students' performance during the learning process. This paper introduces an interactive learning environment for teaching and learning information and communication theory and related courses. The environment integrates several modules to meet the students' different learning styles. It contains a movie-like module, an animated hypertext introductory module that fully explains the fundamental concepts of information and communication theory. Besides those important learning modules, it also contains a self-assessment module that contains a set of interactive tests and examinations. Learners can use the environment as a standalone application or as an applet from within any web browser. Some evaluation experiments and comparative analyses of the results were performed to measure the performance of our environment in the classroom.

This paper provides an historical overview of the theoretical antecedents leading to information theory, specifically those useful for understanding and teaching information science and systems. Information may be discussed in a philosophical manner and at the same time be measureable. This notion of information can thus be the subject of philosophical discussion and the ideas about information may be applied rigorously to a wide range of practical applications where processes are studied. Theoretical Information Science and specific Information Science applications may provide tools by which questions such as "when and what information can be produced"? can be answered, as well as how to implement a system to serve a particular commercial or other specific function. These topics are discussed, and philosophical literature that might serve as a prerequisite to learning Information Science is suggested.

This paper investigates the relationship between blank and non-blank email subject lines on levels of response to a solicitation to participate in an interview, and on participation in a web survey. Email use has grown substantially in recent years, presenting significant opportunity to the empiricist seeking research respondents. However, response to emails may be low because growth in the sheer volume of messages that individuals receive per day has led to a sense of 'email overload', and faced with the challenge of personal email management, many recipients choose to ignore some messages, or do not read them all fully. Drawing on information gap theory, we expected that sending an invitation with a blank subject line would induce a sense of curiosity in recipients that would improve email response and willingness to participate in research studies. However, findings from research with two samples with different propensities to participate in research (academics and business owners) revealed that an email invitation with a blank subject line does not increase overall response rates to a web survey and a face-to-face interview over either an informative subject line or a provocative subject line, but that it does prompt a greater number of active refusals. Based on this finding, recommendations for researchers are outlined.

Many states and school districts are rethinking how they do educational assessment. A few are going further: attempting to build "balanced," "comprehensive," or "next-generation" assessment systems. At the same time, practitioners and researchers have long mulled the purposes and parts such systems should have. But just a few have thought deeply about what a system of assessment actually means. In the words of educational psychologist Theodore Coladarci: "A collection of assessments does not entail a system any more than a pile of bricks constitutes a house." This article focuses on building the house. For states that are building, evaluating, or modifying their assessment systems, the authors offer three criteria to look for: coherence, a theory of action, and efficiency. They developed these criteria after reviewing literature on educational assessment systems, and they have been applying them in work with state and district leaders.

Unstructured data in social media is as part of the "big data" spectrum. Unstructured data in Social media can provide useful insights into social phenomena and citizen opinions, both of which are critical to government policy and businesses decisions. Teachers of business intelligence and analytics commonly use quantitative data from sales, marketing, finance and manufacturing to demonstrate various analytics concepts in a business context. However, researchers have seldom used social media data to analyze social behavior and communication. In this study we aim to demonstrate an assessment structure for teaching social media analytics concepts with the goal of analyzing and interpreting social media content. We base this assessment on forum postings regarding two recent events: the Christchurch earthquake in New Zealand, and the Japanese earthquake and tsunami. The aim of the assessment is to discover social insights. We base the assessment structure on Cooper's Analytics Framework to cover such concepts as term frequency (TF), term frequency-inverse document frequency (TFIDF), data visualization, sentiments and opinions analysis, the Nearest Neighbor K-NN classification algorithm, and Information Diffusion theory. We review how the students performed on the assignment that used this assessment, and we make recommendations for future studies.

In this paper, we draw on Actor-Network Theories (ANT) to explore how material components functioned to create gateways and barriers to a virtual learning network in the context of a professional development module in higher education. Students were practitioners engaged in family learning in different professional roles and contexts. The data comprised postings in the Google+ community, email correspondence, meeting notes, feedback submitted at the final workshop and post-module evaluation forms. Our analysis revealed a complex set of interactions, and suggests multiple ways human actors story their encounters with non-human components and the effects these have on the learning experience. The aim of this paper is to contribute to a more holistic understanding of the components and dynamics of social learning networks in the virtual world and consider the implications for the design of online learning for continuous professional development (CPD).

Information design has practical and theoretical components. As an academic discipline we may view information design as a combined discipline, a practical theory, or as a theoretical practice. So far information design has incorporated facts, influences, methods, practices, principles, processes, strategies, and tools from a large number of disciplines. Information design also needs to incorporate theories, or parts of theories, from other disciplines. This essay presents seven information design theories with more than hundred facts, hypotheses, and postulates.

This study (N = 143) examined the effects of freedom threat on cognitive structures, using recycling as its topic. The results of a 2(Freedom Threat: low vs. high) x 2(Postscript: restoration vs. filler) plus 1(Control) experiment indicated that, relative to the control condition, high freedom threat created a boomerang effect for the targeted attitude (recycling) as the attitude and behavioral intention changed in the opposite direction to the one advocated in the message. For the associated but untargeted attitude (energy conservation), reactance effects were less pronounced. Furthermore, a restoration postscript was examined as a reactance mitigation strategy. The restoration postscript was effective for high- but not low-threat messages. (Contains 2 tables, 5 figures, and 12 notes.)

Tagging systems represent the conceptual knowledge of a community. We experimentally tested whether people harness this collective knowledge when navigating through the Web. As a within-factor we manipulated people's prior knowledge (no knowledge vs. prior knowledge that was congruent/incongruent to the collective knowledge inherent in the tags). As between-factor we manipulated whether people had tag clouds available or not. In line with the Information Foraging Theory and with the Co-Evolution Model of individual learning and collective knowledge building, we found that people's prior knowledge and tag clouds influenced their navigation. Tags which were congruent with people's prior knowledge had a higher probability of being selected. A knowledge test showed that participants adapted their individual conceptual knowledge to the collective knowledge. This incidental learning shows that people harness collective knowledge just by navigation with tag clouds. (Contains 1 table and 3 figures.)

This study relies on information theory, social presence, and source credibility to uncover what best helps people grasp the urgency of an emergency. We surveyed a random sample of 1,318 organizational members who received multiple notifications about a large-scale emergency. We found that people who received 3 redundant messages coming through at least 1 synchronous communication source--for example, phone or face-to-face communication--perceived the urgency of the situation the most quickly, whereas those receiving official messages through asynchronous channels--most often text message--had the lowest sense of urgency. Our findings suggest that by understanding people's reactions to various kinds of redundant communication, organizations can design more strategic emergency messages that capture attention. (Contains 3 tables and 1 figure.)

A major open question in natural language research is the role of communicative efficiency in the origin and on-line processing of language structures. Here, we use word pairs like "chimp/chimpanzee", which differ in length but have nearly identical meanings, to investigate the communicative properties of lexical systems and the communicative pressures on language users. If language is designed to be information-theoretically optimal, then shorter words should convey less information than their longer counterparts, when controlling for meaning. Consistent with this prediction, a corpus analysis revealed that the short form of our meaning-matched pairs occurs in more predictive contexts than the longer form. Second, a behavioral study showed that language users choose the short form more often in predictive contexts, suggesting that tendencies to be information-theoretically efficient manifest in explicit behavioral choices. Our findings, which demonstrate the prominent role of communicative efficiency in the structure of the lexicon, complement and extend the results of Piantadosi, Tily, and Gibson (2011), who showed that word length is better correlated with Shannon information content than with frequency. Crucially, we show that this effect arises at least in part from active speaker choice. (Contains 2 figures.)

A five-month exploratory study was conducted with iOS mobile devices in two Toronto area schools with students in grades 7 through 12. Both classrooms were identified as Special Education classes by the Ontario Ministry of Education, and each student was identified as having exceptionalities requiring additional support and differentiation within the curriculum to support their success. Participants used "MyVoice," a mobile application that is customizable through a website, which allows users to input vocabulary words and link words with pictures. The application can also be used to speak on behalf of users. Based on findings that technology perceived to be "fun" by students has the potential to improve motivation in learning contexts, we aimed to (i) assess the degree to which the use of iOS devices and the MyVoice application affects attention and motivation levels for students with special needs, and (ii) identify factors that had the greatest influence on the integration of the technologies with existing curricula. Results indicated a strong potential for successfully integrating mobile technology within special needs classrooms, with a high-degree of student support for using mobile devices to enhance classroom experiences. The results also highlighted the challenges of incorporating these technologies into curriculum in terms of practicality, teacher comfort, and the limitations of the device. We find that the differentiation enabled by the multi-modal features of the application and device has positive outcomes on student perception of success, and that increased self-confidence in areas of the curriculum fostered a more robust sense of community among special needs students. We conclude with study implications for information processing theory. (Contains 2 figures.)

Tag clouds generated in social tagging systems can capture the collective knowledge of communities. Using as a basis spreading activation theories, information foraging theory, and the co-evolution model of cognitive and social systems, we present here a model for an "extended information scent," which proposes that both collective and individual knowledge have a significant influence on link selection, incidental learning, and information processing. Two experimental studies tested the applicability of the model to a situation in which individual knowledge and collective knowledge were contradictory to each other. The results of the first experiment showed that a higher individual strength of association between a target in demand and a tag led to a higher probability of selecting corresponding links, combined with less thorough information processing for non-corresponding links. But users also adapted their navigation behavior to the collective knowledge (strength of associations of tags) of the community and showed incidental learning during navigation, which resulted in a change of their individual strength of associations. The second experiment confirmed these results and showed, in addition, that the effects also occurred for indirect associations. Altogether, the results show that the extended information scent is an appropriate and fertile model for describing the interplay of individual knowledge and the collective knowledge of social tags. (Contains 6 tables and 8 figures.)

Convergence of the expectation-maximization (EM) algorithm to a global optimum of the marginal log likelihood function for unconstrained latent variable models with categorical indicators is presented. The sufficient conditions under which global convergence of the EM algorithm is attainable are provided in an information-theoretic context by interpreting the EM algorithm as alternating minimization of the Kullback-Leibler divergence between two convex sets. It is shown that these conditions are satisfied by an unconstrained latent class model, yielding an optimal bound against which more highly constrained models may be compared.

The double-well potential is arguably one of the most important potentials in quantum mechanics, because the solution contains the notion of a state as a linear superposition of "classical" states, a concept which has become very important in quantum information theory. It is therefore desirable to have solutions to simple double-well potentials that are accessible to the undergraduate student. We describe a method for obtaining the numerically exact eigenenergies and eigenstates for such a model, along with the energies obtained through the Wentzel-Kramers-Brillouin (WKB) approximation. The exact solution is accessible with elementary mathematics, though numerical solutions are required. We also find that the WKB approximation is remarkably accurate, not just for the ground state, but also for the excited states. (Contains 4 figures and 10 footnotes.)

Our first review article (Wagemans et al., 2012) on the occasion of the centennial anniversary of Gestalt psychology focused on perceptual grouping and figure-ground organization. It concluded that further progress requires a reconsideration of the conceptual and theoretical foundations of the Gestalt approach, which is provided here. In particular, we review contemporary formulations of holism within an information-processing framework, allowing for operational definitions (e.g., integral dimensions, emergent features, configural superiority, global precedence, primacy of holistic/configural properties) and a refined understanding of its psychological implications (e.g., at the level of attention, perception, and decision). We also review 4 lines of theoretical progress regarding the law of Pragnanz--the brain's tendency of being attracted towards states corresponding to the simplest possible organization, given the available stimulation. The first considers the brain as a complex adaptive system and explains how self-organization solves the conundrum of trading between robustness and flexibility of perceptual states. The second specifies the economy principle in terms of optimization of neural resources, showing that elementary sensors working independently to minimize uncertainty can respond optimally at the system level. The third considers how Gestalt percepts (e.g., groups, objects) are optimal given the available stimulation, with optimality specified in Bayesian terms. Fourth, structural information theory explains how a Gestaltist visual system that focuses on internal coding efficiency yields external veridicality as a side effect. To answer the fundamental question of why things look as they do, a further synthesis of these complementary perspectives is required. (Contains 10 figures and 1 table.)

Two auditory lexical decision experiments document for morphologically complex words two points at which the probability of a target word given the evidence shifts dramatically. The first point is reached when morphologically unrelated competitors are no longer compatible with the evidence. Adapting terminology from Marslen-Wilson (1984), we refer to this as the word's initial uniqueness point (UP1). The second point is the complex uniqueness point (CUP) introduced by Balling and Baayen (2008), at which morphologically related competitors become incompatible with the input. Later initial as well as complex uniqueness points predict longer response latencies. We argue that the effects of these uniqueness points arise due to the large surprisal (Levy, 2008) carried by the phonemes at these uniqueness points, and provide independent evidence that how cumulative surprisal builds up in the course of the word co-determines response latencies. The presence of effects of surprisal, both at the initial uniqueness point of complex words, and cumulatively throughout the word, challenges the Shortlist B model of Norris and McQueen (2008), and suggests that a Bayesian approach to auditory comprehension requires complementation from information theory in order to do justice to the cognitive cost of updating probability distributions over lexical candidates. (Contains 16 tables and 9 figures.)

Entropy, a concept derived from thermodynamics and information theory, describes the amount of uncertainty and disorder within a system. Self-organizing systems engage in a continual dialogue with the environment and must adapt themselves to changing circumstances to keep internal entropy at a manageable level. We propose the entropy model of uncertainty (EMU), an integrative theoretical framework that applies the idea of entropy to the human information system to understand uncertainty-related anxiety. Four major tenets of EMU are proposed: (a) Uncertainty poses a critical adaptive challenge for any organism, so individuals are motivated to keep it at a manageable level; (b) uncertainty emerges as a function of the conflict between competing perceptual and behavioral affordances; (c) adopting clear goals and belief structures helps to constrain the experience of uncertainty by reducing the spread of competing affordances; and (d) uncertainty is experienced subjectively as anxiety and is associated with activity in the anterior cingulate cortex and with heightened noradrenaline release. By placing the discussion of uncertainty management, a fundamental biological necessity, within the framework of information theory and self-organizing systems, our model helps to situate key psychological processes within a broader physical, conceptual, and evolutionary context. (Contains 2 footnotes and 2 figures.)

Recent years have seen a surge in accounts motivated by information theory that consider language production to be partially driven by a preference for communicative efficiency. Evidence from discourse production (i.e., production beyond the sentence level) has been argued to suggest that speakers distribute information across discourse so as to hold the conditional per-word entropy associated with each word constant, which would facilitate efficient information transfer (Genzel & Charniak, 2002). This hypothesis implies that the conditional (contextualized) probabilities of linguistic units affect speakers' preferences during production. Here, we extend this work in two ways. First, we explore how preceding cues are integrated into contextualized probabilities, a question which so far has received little to no attention. Specifically, we investigate how a cue's maximal informativity about upcoming words (the cue's "effectiveness") decays as a function of the cue's recency. Based on properties of linguistic discourses as well as properties of human memory, we analytically derive a model of cue effectiveness decay and evaluate it against cross-linguistic data from 12 languages. Second, we relate the information theoretic accounts of discourse production to well-established mechanistic (activation-based) accounts: We relate contextualized probability distributions over words to their relative activation in a lexical network given preceding discourse. (Contains 2 tables, 5 figures, and 5 notes.)

Complex, but specific, tasks--such as chess or "Jeopardy!"--are popularly seen as milestones for artificial intelligence (AI). However, they are not appropriate for evaluating the intelligence of machines or measuring the progress in AI. Aware of this delusion, Detterman has recently raised a challenge prompting AI researchers to evaluate their artefacts against IQ tests. We agree that the philosophy behind (human) IQ tests is a much better approach to machine intelligence evaluation than these specific tasks, and also more practical and informative than the Turing test. However, we have first to recall some work on machine intelligence measurement which has shown that some IQ tests can be passed by relatively simple programs. This suggests that the challenge may not be so demanding and may just work as a sophisticated CAPTCHA, since some types of tests might be easier than others for the current state of AI. Second, we show that an alternative, formal derivation of intelligence tests for machines is possible, grounded in (algorithmic) information theory. In these tests, we have a proper mathematical definition of what is being measured. Third, we re-visit some research done in the past fifteen years for effectively measuring machine intelligence--since some assumptions about the subjects and their distribution no longer hold.

This study tested the effects of two instructional aids in a complex, dynamic environment, specifically, a business simulation. Participants studied (1) a "causal map," which depicted key variables in an interconnected network, (2) a textual outline of the same relationships, or (3) no-aid. With the relevant aid still available, the participants ran the simulation three times. Then, the aid was removed, and the participants ran another three simulations. Both when the aid was available and later when removed, the group receiving the causal map gained a greater market share than the other two groups, which failed to differ. With respect to profits, however, a cross-over interaction appeared. When the aid was available, the causal map group showed lower profits than the other two groups, but, without the aid, the causal map group showed greater profits. The results are discussed in the context of information processing theories of instructional design. (Contains 2 tables and 4 figures.)

On the basis of earlier findings, we (Fiedler & Kareev, 2006) presented a statistical decision model that explains the conditions under which small samples of information about choice alternatives inform more correct choices than large samples. Such a small-sample advantage (SSA) is predicted for choices, not estimations. It is contingent on high constant decision thresholds. The model was harshly criticized by Cahan (2010), who argued that the SSA disappears when the threshold decreases with increasing sample size and when the costs of incorrect decisions are higher than the benefits of correct decisions. We refute Cahan's critique, which confuses normative and descriptive arguments. He neither questioned our theoretical reasoning nor presented empirical counterevidence. Instead, he discarded our model as statistically invalid because the threshold does not decrease with increasing sample size. Contrary to this normative intuition, which presupposes a significance-testing rationale, we point out that decisions are often insensitive to sample size. We also refute Cahan's intuition that ignoring the potential asymmetry of gains and losses creates a serious bias in favor of the SSA. We regret any misunderstandings resulting from our linking the SSA to Bernoulli's law of large numbers. (Contains 1 figure and 2 footnotes.)