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  <front>
    <journal-meta />
    <article-meta>
      <title-group>
        <article-title>Towards Semiology of Teaching Analytics</article-title>
      </title-group>
      <contrib-group>
        <contrib contrib-type="author">
          <string-name>Ravi K. Vatrapu</string-name>
          <email>vatrapu@cbs.dk</email>
          <xref ref-type="aff" rid="aff0">0</xref>
          <xref ref-type="aff" rid="aff1">1</xref>
        </contrib>
        <aff id="aff0">
          <label>0</label>
          <institution>Applied Computing Lab, Norwegian School of Information Technology (NIHT)</institution>
          ,
          <country country="NO">Norway</country>
        </aff>
        <aff id="aff1">
          <label>1</label>
          <institution>Computational Social Science Laboratory (CSSL), Department of IT Management, Copenhagen Business School</institution>
          ,
          <country country="DK">Denmark</country>
        </aff>
      </contrib-group>
      <abstract>
        <p>This paper presents a conceptual framework for designing, implementing, and evaluating notations, representations, and visualizations for teaching analytics.</p>
      </abstract>
      <kwd-group>
        <kwd>cognitive dimensions of notations</kwd>
        <kwd>representational guidance</kwd>
        <kwd>perception of affordances</kwd>
        <kwd>appropriation of affordances</kwd>
        <kwd>teaching analytics</kwd>
      </kwd-group>
    </article-meta>
  </front>
  <body>
    <sec id="sec-1">
      <title>1 Introduction</title>
      <p>Teaching Analytics is a new field of study that seeks to apply visual analytics methods
and tools towards teachers’ dynamic diagnostic decision-making. A central concern in
the emerging field of teaching analytics is the design, development and evaluation of
notations, representations, and visualizations of learning and teaching processes and
products and the enculturation of a “professional vision” for teachers to make the visual
analytics notations, representations, and visualizations meaningful and actionable in
pedagogical settings. Since teachers and learners perceive and act upon representations
of their learning, the notational, emotional, informational and interactive aspects of
representations must be considered in the design and development of teaching analytics
systems.</p>
      <p>This paper presents a conceptual framework to help the study of notational,
emotional, and informational aspects of different kinds of notations, representations,
and interactive visualizations. The primary purpose of this position paper is to present
and discuss three lines of conceptual and empirical work relevant to the design and
evaluation of representations.</p>
    </sec>
    <sec id="sec-2">
      <title>2 Conceptual Framework</title>
      <p>
        Representation as a proxy to information plays a crucial role in design in general. The
nature of representations, their structures and interactions is one of the central concerns
of cognitive science [
        <xref ref-type="bibr" rid="ref16">16</xref>
        ].Philosophically speaking, the function of representation is to
“re-present”. Representation, in the philosophy of mind sense of the term, “is
something that stands for something else”. In teaching analytics, representations
“represent” the ongoing learning of the individual student and/or group of students. The
technological and pedagogical aspects of representations have received significant
conceptual and empirical attention in the fields of human computer interaction and
learning sciences. Three following lines of conceptual and empirical work are
particularly relevant for the design, development, and evaluation of representations in
teaching analytics.
 Cognitive Dimensions of Notations [
        <xref ref-type="bibr" rid="ref1 ref3">1, 3</xref>
        ]


      </p>
      <p>
        Representational Guidance [
        <xref ref-type="bibr" rid="ref11 ref12 ref8">8, 11, 12</xref>
        ]
      </p>
      <p>
        Perception and Appropriation of Socio-Technical Affordances [
        <xref ref-type="bibr" rid="ref14 ref15">14, 15</xref>
        ]
      </p>
      <sec id="sec-2-1">
        <title>2. 1 Cognitive Dimensions of Notations</title>
        <p>
          The cognitive dimensions framework [
          <xref ref-type="bibr" rid="ref1 ref3">1, 3</xref>
          ] can help the conceptualization of the
notational aspects of the teaching analytics solutions. The cognitive dimensions
framework deal with the cognitive affordances of notations with respect to users
engaged in activities. Gibson's ecological optics [
          <xref ref-type="bibr" rid="ref2">2</xref>
          ] and Green and Blackwell's
cognitive dimensions [
          <xref ref-type="bibr" rid="ref1">1</xref>
          ] share conceptual terms such as medium and environment.
Cognitive dimensions of representations, like affordances, are about the action-taking
possibilities and meaning-making opportunities given actor competencies and system
capabilities. The next section presents key concepts in the cognitive dimensions
framework and discusses their relevance to teaching analytics. The following
definitions are taken from Green and Blackwell [
          <xref ref-type="bibr" rid="ref4">4</xref>
          ]:
 Information Artefacts: "the tools we use to store, manipulate, and display
information" (p.5). Information artefacts are further classified as “non-interactive
artefacts” and “interactive artefacts”. Representations are information artefacts
and the static representations studied here are an example of “non-interactive
artefacts”.
 Environment: "The environment contains the operations or tools for
manipulating those marks" (p.8). The environments in the NEXT-TELL context
are the various “dashboards” of the Communication and Negotiation Layer,
ECAAD and such for the different stakeholders.
 Medium: "The notation is imposed upon a medium, which may be persistent,
like paper, or evanescent, like sound"(p.8). In the case of the OLM, the medium
is persistent and dynamically changed.
        </p>
        <p>The cognitive dimensions framework distinguishes four types of user activity.
 Incrementation: "adding further information without altering the structure
in any way" (p.10)
 Modification: "changing an existing structure, possibly without adding new
content"(p.10)
 Transcription: "copying content from one structure to another</p>
        <p>structure;"(p.10)
</p>
        <p>Exploratory Design: "combining incrementation and modification, with the
further characteristic that the desired end state is not known in
advance"(p.10)</p>
        <p>Teaching analytics involves all four kinds of user activity.
2.1.1 Definitions of Cognitive Dimensions














</p>
        <p>Abstraction: "An abstraction is a class of entities, or a grouping of elements to
be treated as one entity, either to lower the viscosity or to make the notation more
like the user’s conceptual structure" (p.24)
Closeness of Mapping: "Closeness of representation to domain" (p.39)
Consistency: "similar semantics are expressed in similar syntactic forms"(p.39)
Diffuseness: "verbosity of language" (p.39)
Error-Proneness: "notation invites mistakes" (p.40)
Hard Mental Operations: "high demand on cognitive resources" (p.40)
Hidden Dependencies: "A hidden dependency is a relationship between two
components such that one of them is dependent on the other, but that the
dependency is not fully visible" (p.17)
Premature Commitment: "Constraints on the order of doing things force the
user to make a decision before the proper information is available" (p.21)
Progressive Evaluation: "work-to-date can be checked at any time" (p.40)
Provisionality: "degree of commitment to actions or marks" (p.41)
Role-Expressiveness: "the purpose of a component (or an action or a symbol) is
readily inferred" (p.41)
Secondary Notation: "Extra information carried by other means than the official
syntax" (p.29)
Viscosity: "Resistance to change: the cost of making small changes"(p.12)
Visibility: "ability to view components easily."(p.34)</p>
        <p>Juxtaposability: "ability to place any two components side by side"(p.34)
The cognitive dimensions of notations defined above should be carefully considered
in the design and implementation of teaching analytics solutions. For example, the
dimensions of “Progressive Evaluation” and “Hidden Dependencies” can both have
implications for designing notations for technology enhanced formative assessment.
Representational aspects in teaching analytics are discussed next.</p>
      </sec>
      <sec id="sec-2-2">
        <title>2.2. Representational Bias</title>
        <p>The system of mental representations “consists not of individual concepts, but of
different ways of organizing, clustering, arranging and classifying concepts and of
establishing complex relations between them” [5, p. 17].</p>
      </sec>
      <sec id="sec-2-3">
        <title>2.2.1 Definition of Internal Representations</title>
        <p>“Internal representations are the knowledge and structure in memory, as
propositions, productions, schemas, neural networks, or other forms” [17, p.
180].</p>
        <p>From a cognitive science perspective, during learning activities information inherent
in internal representations is retrieved from long-term memory and working memory.
2.2.2 Definition of External Representations</p>
        <p>external representations are defined as the knowledge and structure in the
environment, as physical symbols, objects, or dimensions (e.g., written
symbols, beads of abacuses, dimensions of a graph, etc.), and as external rules,
constraints, or relations embedded in physical configurations (e.g., spatial
relations of written digits, visual and spatial layouts of diagrams, physical
constraints in abacuses, etc.) Zhang [17, p. 180]</p>
        <p>
          External representations embody environmental information, and this information
can be “directly picked up” by the human perceptual systems in the Gibsonian
ecological approach [
          <xref ref-type="bibr" rid="ref2">2</xref>
          ].
        </p>
        <p>
          Teaching Analytics systems involve external representations. Representational
salience and constraints of these external representations can influence the cognitive
processes of information retrieval from and subsequent information storage. Suthers’
[
          <xref ref-type="bibr" rid="ref8">8</xref>
          ] conceptual and empirical work on “representational guidance” is highly relevant to
the design of representations for teaching analytics systems.
        </p>
        <p>
          Representational guidance follows from two lines of reasoning. First, the guiding
ontological dimensions of representations— constraint and salience— prompt a user
for what is missing as well for what is present [
          <xref ref-type="bibr" rid="ref9">9</xref>
          ]. The ontological dimensions of
representations are not intrinsically social. Second, external representations play a role
in guiding learning by amplifying certain kind of social interactions [
          <xref ref-type="bibr" rid="ref11">11</xref>
          ] and
knowledge building interactions [
          <xref ref-type="bibr" rid="ref12">12</xref>
          ].
        </p>
      </sec>
      <sec id="sec-2-4">
        <title>2.2.3 Definition of Representational Guidance</title>
        <p>
          “Representational guidance" refers to how these software environments
facilitate the expression and inspection of different kinds of information. [
          <xref ref-type="bibr" rid="ref10">10</xref>
          ]
Representational guidance has tripartite origins in the (a) affordances of a
representational notation, (b) in how that notation is realized in a representational tool
such as software, and (c) in the actual configuration of representational artifacts created
by users of that tool. How notations such as Smilies, Word Clouds, and Traffic Lights
are represented in the software and the actual configuration of representational artifacts
are issues of concern for the design and evaluation of teaching analytics applications.
Finally, the socio-technical interactional aspects in teaching analytics are discussed
next.
        </p>
      </sec>
      <sec id="sec-2-5">
        <title>2.3 Perception and Appropriation of Socio-Technical Affordances</title>
        <p>
          The notion of affordance was introduced by J. J. Gibson [
          <xref ref-type="bibr" rid="ref2">2</xref>
          ]. Gibson was primarily
concerned with providing an ecologically grounded explanation to visual perception.
Affordance is a deceptively simple concept that hides a radical hypothesis. Norman’s
introduction of the concept of “perceived affordance” [
          <xref ref-type="bibr" rid="ref6">6</xref>
          ] brought the notion of
affordance into human computer interaction. Affordances in HCI have largely been
misunderstood as widgets, features and functionalities [
          <xref ref-type="bibr" rid="ref13">13</xref>
          ], despite a crucial
intervention by Norman [
          <xref ref-type="bibr" rid="ref7">7</xref>
          ] himself.
        </p>
      </sec>
      <sec id="sec-2-6">
        <title>2.3.1 Definition of Socio-Technical Affordance</title>
        <p>
          By drawing upon ecological psychology research, Vatrapu [
          <xref ref-type="bibr" rid="ref15">15</xref>
          ] defined a
sociotechnical affordance as “action-taking possibilities and meaning-making opportunities
in a socio-technical system relative to actor competencies and system capabilities.”
        </p>
        <p>With regard to teaching analytics, Perception of Affordances (PoA) refers to the
action-taking possibilities and meaning-making opportunities that become available
(that is, perceivable) to teachers in a given pedagogical situation. Appropriation of
Affordances (AoA) refers to the intentional utilization of the affordances for
actiontaking. AoA refers to the enactment of an interactional practice of teaching analytics
(generative or creative).</p>
      </sec>
    </sec>
    <sec id="sec-3">
      <title>3 Discussion</title>
      <p>In summary, the preliminary conceptual framework presented here can help inform the
design, development, and evaluation of notations (in terms of their cognitive
dimensions), representations (in terms of their saliences and constraints), and
interactive visualizations (in terms of the perception and appropriation of
sociotechnical affordances) for the proposed field of teaching analytics.</p>
    </sec>
    <sec id="sec-4">
      <title>Acknowledgments</title>
      <p>This project is supported by the European Community (EC) under the Information
Society Technologies (IST) priority of the 7th Framework Programme for R&amp;D under
contract number 258114 NEXT-TELL. This document does not represent the opinion
of the EC, and the EC is not responsible for any use that might be made of its content.</p>
    </sec>
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