Writing with Scrivener: A Hopeful Tale of Disappearing Tools,Flatulence, and Word Processing Redemption

There is no writing without technology. Although we are highly aware of writing's mediated nature when asked to learn new writing technologies either as individuals or as a society, we most often ignore these technologies, allowing them to disappear from our consciousness. Not paying attention to our tools can, however, have dangerous consequences. It becomes easy to forget the political, economic, and random forces that influence our choice of technology. Using personal narrative, I explore this tangled relationship between the disappearance of our tools, tool standardization, tool (dis)abilities, and tool design. I tell the story of my four-year-old son's journey to literacy and my discovery of a new type of writing software called Scrivener. Reading the story of Scrivener's development empowered me: I came to see myself as an active participant in the creation of my writing technologies, and I learned to identify when the discomforts of technology should not be ignored. I use these narratives to argue for a posthumanist view of our relationship with technology, a view in which boundaries between humans and technology are blurred, and I offer suggestions on how to adopt a posthumanist perspective toward writing tools in our composition classrooms.     

The quality of group tacit knowledge

Organizational knowledge creation theory explains the process of making available and amplifying knowledge created by individuals as well as crystallizing and connecting it to an organization’s knowledge system. What individuals get to know in their (working) lives benefits their colleagues and, eventually, the wider organization. In this article, we briefly review central elements in organizational knowledge creation theory and show a research gap related to the quality of tacit knowledge in a group. We advance organizational knowledge creation theory by developing the concept of “quality of group tacit knowledge.” Based on this concept, we further develop a comprehensive model explaining different levels of tacit knowledge quality that a group can achieve. Finally, we discuss managerial implications resulting from our model and outline imperatives for future theory building and empirical research.     

Stocks and flows underlying organizations’ knowledge management capability: Synergistic versus contingent complementarities over time

What are the components of a knowledge management (KM) capability and how do they impact firm performance? Based on prior research, we modeled a firm's KM capability in terms of its accumulations of stock – in the areas of human resources, technology infrastructures, and strategic templates – and regulation of flow, via institutionalization and internal and external learning processes. We then considered the extent to which these components complement one another in their impact on two types of firm performance – efficiency, based return on assets, and value creation, assessed as Tobin's q (the ratio of the capital market value of the firm to the replacement value of its assets). We posited differential types of stock-flow complementarities across these two performance outcomes over time – stable, positive effects on firm efficiency, synergistic complementarity, and initially positive, but subsequently negative effects on value creation, contingent complementarity. Data gathered from 218 Korean firms supported this premise. Implications for practice in the evolving fields of organizational capability and complementarities were explored.     

Digital new market creation by incumbent firms: A political lens on the effect of formalization on agility

Digital new market creation has several advantages for incumbent firms (hereafter referred to as ‘incumbents’) that they seek to exploit by using formalization and implementing agility in their new product development (NPD). We introduce the construct of NPD decision agility encompassing the dimensions of sensemaking, speed, and iteration. However, research reveals heterogeneous insights into formalization’s suitability for digital new market creation and NPD decision agility. In response to this research gap, we test our hypotheses by applying a behavioral lens to a sample of 129 incumbents. We reconcile these heterogeneous insights on innovation by showing that formalization increases digital new market creation, but has more fine-grained effects on NPD decision agility. Although improving sensemaking and reducing iteration, formalization has no effect on speed. Furthermore, political behavior increases formalization’s negative effect on iteration. We contribute to research digitalization and agility at the intersection of information systems and innovation management by reconciling these heterogeneous insights.     

Prioritized assertional-based removed sets revision of <Emphasis Type="Italic">DL</Emphasis>-<Emphasis Type="Italic">Lite</Emphasis> belief bases

In real world applications, information is often provided by multiple sources having different priority levels reflecting for instance their reliability. This paper investigates ”Prioritized Removed Sets Revision” (PRSR) for revising stratified DL-Lite knowledge bases when a new sure piece of information, called the input, is added. The strategy of revision is based on inconsistency minimization and consists in determining smallest subsets of assertions (prioritized removed sets) that should be dropped from the current stratified knowledge base in order to restore consistency and accept the input. We consider different forms of input: A membership assertion, a positive or a negative inclusion axiom. To characterize our revision approach, we first rephrase Hansson’s postulates for belief bases revision within a DL-Lite setting, we then give logical properties of PRSR operators. In some situations, the revision process leads to several possible revised knowledge bases where defining a selection function is required to keep results within DL-Lite fragment. The last part of the paper shows how to use the notion of hitting set in order to compute the PRSR outcome. We also study the complexity of PRSR operators, and show that, in some cases, the computational complexity of the result can be performed in polynomial time.     

Using decision tree modelling to support Peircian abduction in IS research: a systematic approach for generating and evaluating hypotheses for systematic theory development

Since their early development, computers have had a profound impact on how we conduct modern scientific research. The disciplines of mathematics and operations research are perhaps the earliest to be dramatically transformed by information technology. However, over the years, computing technologies have provided many new opportunities for information processing, problem solving and knowledge creation. In this paper, we explore the potential of data mining technology for providing support for systematic theory testing based on Peirce's theory of abduction. We propose a data mining approach to abducting and evaluating hypotheses based on Peirce's scientific method. We believe that this approach could assist scientist to more efficiently explore alternative hypotheses for existing theories. We demonstrate our approach with empirical observations collected using instruments from the well known user performance area of information systems research.     

Autobiographical Accounts of Students' Experiences Learning Mathematics: A Review

ABSTRACT

In this article, we review published literature that draws on autobiographical accounts of students' experiences learning mathematics. We summarize the main findings of the target literature and present recommendations for further research that will extend this field. Our review indicates that autobiographical and narrative methodological approaches have the potential to occasion important advances in our knowledge of students' experiences learning mathematics. However, relative to accounts of preservice teacher learning, there is a paucity of published research that documents the mathematics learning experiences of kindergarten to Grade 12 students.     

Learning from syntax generalizations for automatic semantic annotation

Nowadays, there is a huge amount of textual data coming from on-line social communities like Twitter or encyclopedic data provided by Wikipedia and similar platforms. This Big Data Era created novel challenges to be faced in order to make sense of large data storages as well as to efficiently find specific information within them. In a more domain-specific scenario like the management of legal documents, the extraction of semantic knowledge can support domain engineers to find relevant information in more rapid ways, and to provide assistance within the process of constructing application-based legal ontologies. In this work, we face the problem of automatically extracting structured knowledge to improve semantic search and ontology creation on textual databases. To achieve this goal, we propose an approach that first relies on well-known Natural Language Processing techniques like Part-Of-Speech tagging and Syntactic Parsing. Then, we transform these information into generalized features that aim at capturing the surrounding linguistic variability of the target semantic units. These new featured data are finally fed into a Support Vector Machine classifier that computes a model to automate the semantic annotation. We first tested our technique on the problem of automatically extracting semantic entities and involved objects within legal texts. Then, we focus on the identification of hypernym relations and definitional sentences, demonstrating the validity of the approach on different tasks and domains.     

Cards-to-presentation on the web: generating multimedia contents featuring agent animations

With the goal of supporting the knowledge circulation and creation process in a society, we have studied story-based communication in a network community. On the basis of this research motivation, this paper proposes a web-based multimedia environment called Stream-oriented Public Opinion Channel (SPOC), which enables novice users to embody a story as multimedia content and distribute it on the Internet. The system produces digital camera work for graphics and video clips and automatically generates agent animations according to linguistic information in a text. The findings of our evaluation experiments show that SPOC is easy for novice users to learn and use, suggesting that this system can reduce a user's cost in creating multimedia content and encourage communication in a network community.     

COMPUTERIZED METHODOLOGY FOR THE EVALUATION OF LEVEL OF KNOWLEDGE

This article considers, the problem of a formal representation and identification of an individual's level of knowledge. Knowledge is considered as the systematic structurization of information received in perception. The computer implemented methodology reported here includes

? Representation of the initial information (data) in the form of interlinked information structures producing a systematic hierarchical dynamic network.

? Relative evaluations of the level of each individual's knowledge in terms of their semantic network's macrosystemic informational complexity (MC).

The results of an empirical study utilizing this methodology is reported. 331 high school students from eleven classrooms completed a pair-wise similarity rating task of ten mathematics terms along with a standardized math achievement test. The information contained in the similarity data was given an algorithmic representation, which in turn yielded a minimal spectrum of the information nodes making up a systemic representation in the form of a hierarchical network. The prospects of tailoring this methodology such that a student could receive graphical feedback and numerical evaluations of their level of knowledge is discussed. This approach clearly has applications in the areas of computer-based learning and intelligent computer-assisted instruction. The novelty of the solutions to the problems addressed by this work include

? A direct informational measure of the generation of knowledge.

? Computer-based restoration of the logical connections made in the process of reflection and accommodation (which introduces the possibility to control and monitor this process).

? A modern mathematical method, based on the identification of an informational law for concrete objects, which can represent the latent bound information harbored in systems of dynamic structure.

? An objective evaluation of the logical connections within a hierarchical network in terms of Me.

This approach introduces a new research tool to cognitive science, cognitive psychology, educational psychology, and other related fields of study.     

Designing priors for robust Bayesian optimal experimental design

Building mathematical models is a common task in process systems engineering, which requires estimation of model parameters as the final step of modeling exercise. Model based experimental design has evolved as a potential statistical tool for reducing uncertainties in parameter estimates. Often a huge volume of process information is generated as an end result of an experimental design. Designing optimal experiments based on current or prior process knowledge is still an open research problem. This paper deals with how information, available a priori, can be organized and systematically used for designing robust Bayesian dynamic experiments, in the presence of process constraints. The designed experiments are ‘robust’ to a poor choice of nominal parameter values. Several novel techniques for organizing a priori process knowledge are explored from a theoretical view point. The influence of proposed prior designs on parameter estimates is demonstrated on a semi-continuous baker's yeast fermenter problem.     

Efficiency of learning environment using GeoGebra when calculus contents are learned in collaborative groups

In this paper we present a modern approach of teaching mathematics based on the computer supported collaborative learning (CSCL) of calculus contents. The collaborative learning was used in calculus course at the University of Novi Sad, Serbia, for examining functions and drawing their graphs. In 2012 the authors decided to improve the collaborative learning introducing GeoGebra application. Small four member groups were formed by using Kagan's (1994) principles. Two groups of students, the experimental, and the control one were observed. The students in the experimental group learned with the help of GeoGebra, and the students in the control group learned without using GeoGebra.Comparison between those two groups of the first year calculus students, regarding their way of learning and the results achieved, is described below. Before the students' collaborative learning, they were tested with a pre-test and their knowledge necessary for examining functions was verified. The pre-test showed that there was no significant statistical difference between the experimental and the control group. The experimental group worked with the help of the computer and the control one without it. After the collaborative learning, the students were tested with a test (colloquium) and the results of the experimental group were significantly better than the results of students in the control group. At the end of the course the students did their exams (post-test), and the results of the experimental group were significantly better than the results of students in the control group.Some students from the experimental group had to answer questions in an interview related to the use of GeoGebra during their collaborative learning. In order to see the students' difficulties in solving problems, students in the experimental group were asked to cross out incorrect parts of solutions, not to erase them. The teachers reviewed the students' tasks done during the collaborative learning and after that the students who had corrected their mistakes were invited for an interview about using GeoGebra for overcoming their difficulties. Based on the students' results in the tests, answers in the questionnaire and in the interview, it can be concluded that GeoGebra has enabled an easier learning of this material. The GeoGebra package enables the students to check whether each step in the process of solving a task was correctly done or not. The results of our research show that GeoGebra can help those students having insufficient knowledge (necessary for solving those tasks) to improve it.We can say that our research shows that the students' learning achievement in examining functions and drawing their graphs is better when they use GeoGebra, working in collaborative groups than without using it. Also, GeoGebra enables creation of effective learning environment for examining functions and drawing their graphs.     

Understanding digital transformation: A review and a research agenda

Extant literature has increased our understanding of specific aspects of digital transformation, however we lack a comprehensive portrait of its nature and implications. Through a review of 282 works, we inductively build a framework of digital transformation articulated across eight building blocks. Our framework foregrounds digital transformation as a process where digital technologies create disruptions triggering strategic responses from organizations that seek to alter their value creation paths while managing the structural changes and organizational barriers that affect the positive and negative outcomes of this process. Building on this framework, we elaborate a research agenda that proposes [1] examining the role of dynamic capabilities, and [2] accounting for ethical issues as important avenues for future strategic IS research on digital transformation.     

Artist Space

Abstract

This paper addresses the process of patterning reconfigurable video narrative using architectural theory, through a case-study of practice-based research on the interactive, reconfigurable small-screen movie Gormenghast Explore. It focuses on the topography of cinematic narrative as architectural construction, refashioning Kevin Lynch's urban categories and Christian Norberg-Schulz's concept of place to support a design ontology for dramatic fictive narrativity. This architectural framework provides an effective representation for both navigable narrative content and 3D environment and interface.     

Modeling use of enterprise resource planning systems: a path analytic study

In this research, we evaluated user participation and involvement in the context of enterprise resource planning (ERP) systems. Since ERP systems are enterprise-wide in scope, these systems have a high level of complexity, and require a different implementation methodology. While most studies analyze implementation at an organization or industry level, there is a dearth in research in ERP system adoption at the individual or user level. In our study, we examine ERP system acceptance at the individual level. In this research, we expected to find differences in the nature of user participation and involvement in ERP compared to other information systems. Using Barki and Hartwick's extension of the theory of reasoned action, a revised model was developed and tested empirically. While Barki and Hartwick's model explains user behavior vis-à-vis user participation and involvement, a more parsimonious model demonstrates that usage dynamics in ERP implementation are different. We complemented our statistical analysis by three case studies. Based on our results we believe that, given the nature of ERP and its implementation, traditionally formalized links between influencers of users' attitude and involvement may need to be revised. We have discussed why we need to seek alternate forms of influencers. In doing so, we suggest that investments be made in preparatory work practices and employee development prior to ERP decisions. Such investments are complementary to information technology and are widespread throughout the firm. We believe that such investments will play a significant role in influencing the attitude of users toward any system and also their involvement.     

An empirical study of narrative imagery in implicit and explicit contexts

This study investigates if imagery is an inherent construct to narrative by playing a role in storytelling and comprehension. Visualization activities consist of ones that depend on pictures or physical objects and those do not depend on extraneous visual artifacts. The understandings of both types of visualization will contribute to their application and integration. In light of rapid development of technology and drastic increase of multimedia representations in social communication, applying storytelling approach to system design is increasingly relevant to many researchers who are eager to bring visual thinking to the classroom, alternative to applying physical visual artifacts. In this study, we looked into the cognitive process evoked in the comprehension of narrative and its similarity to imagery as an individual cognition. We transformed a course into conversational narrative and participants were randomly assigned into three sections, two were in narrative text and one was in expository text. Sections 1 and 2 were in narrative text, but only participants from section 1 were prompt for image creation before writing essays. Section 3 was in expository text and participants were also prompt for image creation before writing essays. The independent samples t-test was used to compare the mean scores of three groups on creativity score and word total across the sections. Our study found that narrative was able to activate the imagery world of the participants without giving them further instructions explicitly suggesting so. The implicit imagery context created by reading narratives had a stronger impact on creativity than that of explicit imagery creation context that did not involve of narrative comprehension. The study suggests that narrative innately provides some sort of control to its user cognitively and can be integrated with other types of media in design.     

考虑知识溢出下产业集群创新网络协同知识创造决策分析

协同知识创造对于企业维持和获取竞争优势具有重要作用,但是知识外溢会对企业的竞争力造成威胁,从而使企业在创新网络协同知识创造决策时陷入两难困境.鉴于此,通过构造由一个核心企业和n个从属企业组成的创新网络在协同知识创造过程中知识投入决策Stackelberg博弈模型,引入知识内溢系数、私有知识、知识外溢损失等变量,探讨知识溢出下,网络成员的知识投入决策和知识产出分配问题.研究结果表明:核心企业与从属企业的知识投入比和知识投入总量与协同知识创造绩效和知识内溢收益之和有关,而与私有知识外溢的损失无关;集群创新网络协同知识创造机制得以运行的条件是核心企业的知识创造收益(即知识创造绩效与知识内溢收益之和)足够大;核心企业的知识投入比与其边际收益和知识内溢系数正相关,与从属企业的边际收益和知识内溢系数负相关;协同知识创造过程中从属企业会根据其边际收益和知识内溢系数按比例分配知识的投入比.     

Rule-based expert systems to support step-by-step guidance in algebraic problem solving: The case of the tutor PAT2Math

In order for an Intelligent Tutoring System (ITS) to correct students’ exercises, it must know how to solve the same type of problems that students do and the related knowledge components. It can, thereby, compare the desirable solution with the student’s answer. This task can be accomplished by an expert system. However, it has some drawbacks, such as an exponential complexity time, which impairs the desirable real-time response. In this paper we describe the expert system (ES) module of an Algebra ITS, called PAT2Math. The ES is responsible for correcting student steps and modeling student knowledge components during equations problem solving. Another important function of this module is to demonstrate to students how to solve a problem. In this paper, we focus mainly on the implementation of this module as a rule-based expert system. We also describe how we reduced the complexity of this module from O(n^d) to O(d), where n is the number of rules in the knowledge base, by implementing some meta-rules that aim at inferring the operations students applied in order to produce a step. We evaluated our approach through a user study with forty-three seventh grade students. The students who interacted with our tool showed statistically higher scores on equation solving tests, after solving algebra exercises with PAT2Math during an approximately two-hour session, than students who solved the same exercises using only paper and pencil.