 
    e-Proofs: Design of a Resource to Support Proof Comprehension in Mathematics
    Lara Alcock & Nicola Wilkinson
      The University of Loughborough
  
    Abstract
1
    This paper presents a theoretical basis for the design of e-Proofs,
      electronic resources to support proof comprehension in undergraduate
      mathematics. To begin, we frame the problems of teaching for proof
      comprehension, giving research background and an argument about what
      teacher-centred lecturing does not, and cannot, do to address these. We
      then describe e-Proofs, discuss the way in which they have been used in
      an Analysis course, and review their limitations and affordances as part
      of an overall educational experience. Finally, we briefly describe the
      development of a web-based tool for constructing e-Proofs, ways in which
      this tool will be used to different pedagogical ends, and associated
      research activity.
   
  Introduction
2
  Proofs in undergraduate mathematics
  In many undergraduate mathematics lectures, the lecturer spends a
    large proportion of the time presenting proofs of theorems (Weber,
    2004). Much of the prose in textbooks also consists of proofs (Raman,
    2004), and there is a clear assumption that students will learn a great
    deal of mathematics by reading the proofs of others (Selden &
    Selden, 1995). This paper is about what this entails and the design of
    an electronic resource to support it. This introduction presents an
    example of the type of proof students encounter and gives some first
    observations about its structure and about the thinking required to
    understand it.
  
    
    
    
      Students in a proof-based lecture course would typically be
        presented with proofs like that for Rolle’s Theorem as shown in Figure 1. Most first courses in Analysis would include
        this theorem and a version of the proof, which is not atypical of proofs
        at this level; some would be shorter but some would be longer and more
        complicated, and such a course might involve around 20 such proofs.
        Students might also be shown an accompanying diagram; one for Rolle’s
        Theorem is shown in Figure 2.
      For many people the diagram will confirm intuitively that the
        theorem is correct. The proof is nonetheless provided, with the
        expectation that the student will attempt to understand it. This
        expectation is probably different from earlier mathematics courses in
        which the student may have been asked to study and apply theorems (eg. (Hughes-Hallett, Gleason et. al. [1994] introduce the Mean Value
        Theorem without proof and use it in exercises on Taylor polynomial
        approximations). It is, however, consistent with the aim that students
        should come to understand mathematical theories as systems of
        interconnected results, all proved on the basis of agreed definitions
        and forms of reasoning (cf. Bell, 1976; de Villiers, 1990).
     
   
  
  Understanding a proof: Some first observations
  This proof is typical in that both the theorem and the proof are
    written using a combination of words and algebraic notation, the latter
    of which can be read out loud so that the whole proof consists of
    well-formed English sentences. Clearly, a student will need to be
    familiar with the names and meanings all of these words and symbols in
    order to read the proof fluently and understand it (notation used is
    summarised in Appendix
    A).
  The proof is structured so that it begins with the assumptions
    from the theorem premises and ends with the conclusion. The first three
    lines prove that there exists a point x1 at which f has a minimum
    on the interval – all function values on the interval are greater than or
    equal to f(x1) – and a point at which it has a maximum. The remaining lines
    rely on this information, and collectively form a subproof by cases
    that, whether or not this maximum and minimum occur at the endpoints,
    there is necessarily a point at which the derivative of the function is
    zero. For a full understanding, the reader will need to recognise this
    structure.
  The proof explicitly quotes two other theorems, the Extreme Value
    Theorem and the Interior Extremum Theorem, both of which would probably
    have been proved earlier in the same course and are used without being
    written out. The proof also uses various defined concepts. Again, these
    definitions are not written out in the proof, and unlike the theorems,
    they are not explicitly invoked. Indeed, some (maximum and minimum) are
    used directly, but some (continuity and differentiability) are built
    into the assumptions of the quoted theorems. For a full understanding,
    the reader will therefore need to recall these definitions and theorems
    and examine the ways in which they are being used (all of these
    definitions and theorems are listed in Appendix A).
  Clearly it is not a trivial exercise to identify this structure
    or to recall and examine the relevant information. In the next section,
    we give a more detailed theoretical breakdown of the skills this
    requires and describe research indicating the degree to which we can
    expect students at the undergraduate level to have these skills.
  Theoretical issues: Framing the problem
3
  Literature on students and proof
  The literature on students’ experience of mathematical proof has
    documented difficulties in constructing proofs (eg., Harel & Sowder,
    1998; Moore, 1994; Weber, 2001) and in validating proofs or assessing
    whether types of argument are acceptable (eg. Healy & Hoyles, 2000; Knuth, 2002; Raman, 2003; Recio & Godino, 2001; Segal, 2000; Selden
    & Selden, 2003). This work is relevant to proof comprehension as
    discussed below, although various authors have noted that the issue of reading proofs has received comparatively little research attention (Hazzan
    & Zazkis, 2003; Mamona-Downs & Downs, 2005; Selden & Selden,
    2003).
  Approaches to proof comprehension
  Not everyone goes about proof comprehension in the same way, and
    one approach is to examine how the statements and arguments relate to
    particular examples or diagrams. Weber (2008), for instance, documented
    cases in which mathematicians used examples while validating proofs, and Movshovitz-Hadar and Hazzan (2004) reported on a lecturer who used an
    extended example to motivate and explain a theorem and proof in group
    theory. Such a tactic might be called a semantic approach, by analogy
    with semantic proof construction strategies described in Weber and
    Alcock (2004) and Alcock and Inglis (2008). e-Proofs, however, focus on
    supporting comprehension by explicating the relationships among the
    theorem premises and conclusions, the individual lines of the proof, and
    external information such as established definitions and theorems. This
    might be considered a syntactic approach, again by analogy with a proof
    construction strategy in which the reasoner proceeds “by moving between
    agreed configurations such as definitions and theorems statements by
    applying the rules of logic, standard proof frameworks and so on”
    (Alcock & Inglis, ibid. p.115).
  In the next sections we give a theoretical breakdown of a
    syntactic approach to proof comprehension, organising this discussion
    around Lin and Yang’s characterisation of facets of proof comprehension.
    Lin and Yang identified these facets on the basis of existing literature
    and interviews with mathematicians and mathematics teachers (Yang &
    Lin, 2008). They used them to design proof comprehension questions for a
    purportedly student-produced proof in geometry, and used the resulting
    test as part of an empirical study (Lin & Yang, 2007). For each
    facet we do the following: 1) describe its meaning and its
    operationalisation via comprehension test questions; 2) compare with
    observations about the Rolle’s Theorem proof from the introduction and
    with proof comprehension questions from Conradie and Frith (2000) based
    on a standard proof that is irrational (reproduced in the Appendix B);
    and 3) discuss what other research literature tells us about relevant
    student competencies.
  Basic knowledge
  Lin and Yang’s first facet is called basic knowledge,
    which they operationalised as recognising the meaning of a
    symbols in a figure and explaining/recognising the meaning of a
    property (Lin & Yang, 2007 p.750). They tested basic knowledge via
    questions that asked for labelling figures, comparing angles etc. Conradie and Frith (2000, p.227) included comparable questions on
    background conceptual or procedural knowledge, for instance requesting
    definitions:
  
  As noted in the introduction, basic knowledge of definitions and
    earlier theorems would also be necessary to understand the proof of
    Rolle’s Theorem. In addition, students some way into an undergraduate
    degree would be expected to be fluent in various forms of algebraic
    manipulation, to be able to state the meaning of symbols like “∃” and to
    be able to correctly interpret sentences containing these.
  Unfortunately, we cannot expect that students will necessarily
    have the required background knowledge. New definitions and theorems
    appear on a daily basis in undergraduate courses, and it is unrealistic
    to think that students will have all of these at their fingertips. Also,
    research indicates that undergraduates are often inaccurate in
    interpreting the logic of mathematical statements involving conditionals
    and quantifiers (Dubinsky & Yiparaki, 2000; Epp, 2003; Hazzan &
    Leron, 1996; Selden & Selden, 1995). Further, students often do not
    attend to definitions, instead relying on concept images (Vinner, 1991),
    even when working with concepts for which they have minimal prior
    experience (Edwards & Ward, 2004). This is important because of the
    way in which precise statements of definitions are used in proofs. For
    instance, in the Rolle’s Theorem proof, the formal definitions of
    minimum and maximum are combined and used to formulate line 3; a student
    who has only an intuitive idea that the maximum occurs “where the
    function is biggest” is not likely to recognise this. Of course, seeing
    mathematical language and definitions used in proofs is one way in which
    students learn about them, but inexperience will impede comprehension of
    any given proof in the meantime.
  Logical status (inferring warrants)
  Lin and Yang’s second facet is called logical status,
    which they operationalised as recognising a condition applied
    directly, judging the logical order of statements and recognising
    which properties are applied (Lin & Yang, 2007 p. 351). They tested
    this via questions about possible reordering of lines and about which
    properties are used at different stages. Conradie and Frith (2000,
    p.227) included questions with similar aims, for example:
  
  Such questions require two things. First, the reader needs to
    shift their focus from the content of each statement to its status; to
    see statements in the proof as premises and conclusions, and indeed to
    be able to treat the same statement as conclusion at one stage and
    premise at the next (Duval, 2007). Second, the reader must infer
    the warrant that the proof’s author is using in order to justify the new
    statement. We use this term in the sense of Weber and Alcock (2005), who
    use a restricted version of Toulmin’s (1958) scheme in which an argument
    is seen as composed of data, warrant and conclusion. For instance, in
    the second of Conradie and Frith’s questions, the data is that 5 is a
    factor of m2 and the conclusion is that 5 is a
    factor of m. Both of these appear in the proof. The question
    asks the reader to infer the warrant, which does not. Weber and Alcock
    point out that this is common: readers often have to infer warrants
    because these are often implicit in textbook proofs. In fact, when
    inferring warrants, the focus might need to be broadened to other lines
    of the proof, because it is common for the data to be distributed across
    the preceding lines and the theorem premises. For instance, in the
    Rolle’s Theorem proof, use of the Interior Extremum Theorem requires the
    function to have a maximum or minimum on the interior of an interval, as
    assumed in line 7, and requires the function to be differentiable on
    that interval, as assumed in line 1.
  Again, it is not realistic to assume that students will be able
    to do all of this easily. First, students will be accustomed to everyday
    argumentation in which the focus is on the content of the statements
    rather than on their status within a larger structure (Duval, 2007).
    Second, a student who does not accurately interpret conditional and
    quantified mathematical statements is unlikely to infer warrants
    appropriately, and a student who is not conversant with earlier
    definitions and theorems will be further hampered in this process.
    Third, and more importantly, research on proof validation indicates that
    students may not even attempt to infer warrants when reading
    proofs. Selden & Selden (2003), for instance, found that students
    who were asked to check the validity of short number theory proofs often
    did not notice when one line did not follow from the line above.
    Similarly, Alcock and Weber (2005) found that only two out of 13
    undergraduate students correctly inferred and rejected a fairly
    straightforward invalid warrant in an Analysis proof. Weber (2009) found
    that 28 undergraduates who had completed a transition-to-proof course
    rarely spent more than two minutes deciding whether purported proofs
    were valid. They were often prepared to make a validity judgment despite
    acknowledging their own incomplete understanding; at least some appeared
    to believe it to be the responsibility of the proof’s author to spell
    out all the details, so that the fault in understanding in these cases
    lay with the author and not with the reader. This indicates that a
    substantial number of students may not read proofs in a way that is
    likely to lead to understanding of their logic.
  Summarisation (identifying larger scale structure)
  Lin and Yang’s third facet is summary, which they
    operationalised as identifying critical procedures, premises or conclusions and indentifying critical ideas of a
    proof (Lin & Yang, 2007, p.751). They tested this via questions
    about what the proof shows and about identifying a significant
    intermediate result and how it is used. Conradie and Frith (2000,
    p.227-228) again included questions with similar aims, such as:
  
    - 
      What method of proof is used here? 
- 
      Which assumption is contradicted, and how does the theorem
        follow from this? 
The introduction to this paper discussed such overall structure
    for the proof of Rolle’s Theorem. Duval (2007, p.142) captured another
    such structure with the aid of a tree diagram for a geometry proof in
    which the theorem premises are used to prove two independent
    intermediate results, which are then put together to arrive at the
    required conclusion.
  Identifying such structure requires understanding the proof at a
    more global level, looking for major steps, subproofs and standard
    structures within these subproofs or the proof as a whole. Again,
    accurate interpretation of conditional and quantified statements will be
    required to do this fully. Knowledge of definitions will be highly
    relevant because statements like “Prove that x is an X”
    need to be interpreted as “Prove that x satisfies the
    definition of X”(cf. Alcock and Simpson, 2002), meaning that
    definitions often form structures for proofs. Selden and Selden (2003) discussed this point in detail, arguing that definitions and other
    statements often dictate the top-level structure of a proof. Difficulty
    in identifying larger-scale structures is likely to be exacerbated by
    confusion over particular argument structures such as proof by induction
    (eg., Dubinsky, 1987; Harel, 2001) or contradiction (eg., Antonini &
    Mariotti, 2008).
  Generality
  Lin and Yang’s fourth facet is generality, which they
    operationalised as justifying correctness and identifying
    what is validated by the proof (Lin & Yang, 2007, p.751). They tested this via
    questions that asked whether the purported proof was valid and whether
    it proved that the target statement was sometimes or always correct.
    Conradie and Frith included a question in which a proof appeared without
    its corresponding theorem and the student was asked what had been proved
    (Conradie & Frith, 2000, p.228).
  Questions of this type might seem irrelevant to a lecture in
    which a correct theorem and proof is presented, so that there is no
    question of validity or scope. However, we would still want the student
    to understand that the proof does in fact prove the specified statement,
    and this might be problematic. Selden and Selden (2003) found that in
    validating short purported number theory proofs, only two out of eight
    students initially spotted that one of these was a proof of the converse
    of the target theorem (also incorporating a notational error). Weber
    (2009) reported similar results. It is worth noting that in these
    studies, along with that of Alcock and Weber (2005), many of the
    arguments used were only four lines long. This is substantially less
    than the length of many proofs presented in undergraduate lectures.
  Combining skills
  Describing these facets in this order emphasizes that some are
    more local (understanding particular lines) and others more global
    (understanding overall structures). This should not be taken to mean
    that one proceeds in understanding a proof in this order. Weber (2008),
    for instance, found that mathematicians faced with proofs in an
    unfamiliar area typically began by identifying the global structure and
    then proceeded to a line-by-line check. Clearly, however, developing a
    full understanding of a proof is a complicated process, and there is a
    lot of scope for proofs to be poorly understood.
  Practical issues: The problem of lecturing
4
  Research-based responses to difficulties with proof
  In recognition of students’ difficulties, mathematics educators
    have suggested various ways of making proofs more accessible. Rowland
    (2001), for instance, suggested that proofs using a generic example
    might be more comprehensible than fully general proofs. Harel (2001) described an approach to proof by induction that begins with repeated
    experience of constructing recursion arguments. Leron (1985), described
    both an approach to contradiction that involves working first on the
    central constructive idea, and a general approach in which a proof task
    is broken into chunks to highlight its overall structure (Leron, 1983).
    Others have focused on student-centered reform-oriented instruction in
    which entire courses have been redesigned in order to give students more
    responsibility for constructing proofs (eg., Alcock & Simpson, 2001; Rasmussen and Marrongelle, 2006; Zandieh, Larsen and Nunley, 2008).
  However, neither type of research has not had a strong influence
    on how proofs are presented. In the latter case this is partly because
    of resource issues: many lecture classes involve well over 100 students,
    a situation that does not lend itself to involving the students as a
    coherent knowledge-building community and that is not going to change
    any time soon. While large lectures do not have to be run entirely on a
    transmissionist model (eg., Biggs & Tang, 2007), lecturer-provided
    explanations are likely to remain a mainstay of the undergraduate
    mathematical experience for the foreseeable future.
  Explanations in lectures
  In presenting a proof, a lecturer typically writes it on the
    board one line at a time, giving additional explanation about why each
    line is valid. He or she might also give an overview of the argument,
    state rationales for certain approaches, point out sections that achieve
    different subgoals, and relate these to the overall structure of the
    theorem (eg., Movshovitz-Hadar & Hazzan, 2004; Weber, 2004).
  These explanations may be clear and informative, but there are
    several problems with expecting them to lead to proof comprehension.
    First, they require the student to draw on background knowledge,
    recognise and validate cited warrants, and recognise larger scale
    structures and generality, all in rapid succession. Second, although the
    lecturer will try to facilitate this process with reminders, hand
    gestures and so on, the student’s attention may not be directed
    precisely enough. Third, even if a student’s attention is in the right
    place(s), they may not be able to grasp the logical relationships
    quickly enough to understand them, especially if this involves recalling
    an earlier theorem or results from earlier lines. Fourth, each student
    is likely to have slightly different difficulties in following the
    explanation, and the lecturer cannot take a few minutes to pause for
    each of these. Fifth, whatever explanation is offered is ephemeral and
    is typically no longer available when the student comes to re-read their
    lecture notes. This means that even a dedicated student who pays
    attention in lectures must reconstruct it during independent study.
  Once these problems are recognized, one practical solution would
    be to record the lecture. This would allow a student to see and hear
    explanations again, but does not address the problems of directing
    attention precisely or of seeing relationships in real time. Also, there
    may be slips and hesitations in the spoken explanation, visuals and
    audio are unlikely to be optimally clear, and there may be extraneous
    distracters in either. Another solution would be to provide additional
    written information to accompany the proof. This is sometimes done,
    perhaps in a two-column format as by the professor studied by Weber
    (2004). However, giving more detail might obscure the structure of the
    proof, as other authors have noted: “to make a proof too detailed would
    be more damaging to its readability than to make it too brief” (Davis
    & Hersh, 1985, p.73) and “[the student may] have difficulty
    distinguishing supplementary and explanatory remarks from the proof
    itself” (Selden and Selden, 1995, p. 140). Annotations and further
    explanation might well be useful, but we suggest that adding these as
    additional text is not an optimal delivery method, and that a
    technological solution can do better.
  e-Proofs
5
  Initial design
  
    
    
    
      e-Proofs are designed to address theoretical proof comprehension
        issues within the practical context of traditional lectures, by making
        the structure and reasoning used in a proof more explicit without
        cluttering its presentation. Each e-Proof consists of a sequence of
        screens such as that shown in Figure 3. Each screen shows the theorem
        and the whole proof, with much of the latter “greyed out” to focus
        attention on particular lines. Relationships are highlighted using boxes
        and arrows, and each screen is accompanied by an audio file which
        students can listen to as many times as they wish.
      The screen in Figure 3 comes from what we have termed the line-by-line version of this e-Proof. We also constructed chunk versions, the
        aim of which is to focus attention on the global structure of the proof
        by breaking it into relatively self-contained sections or subproofs. Figure 4 shows a screen from the chunk version of the same e-Proof.
      Improvements in a new version
      The e-Proof screens shown above were constructed by using Beamer
        to convert a LaTeX file into a pdf presentation, which was then
        annotated and separated into screens. The audio was recorded using
        Audacity. This content was then uploaded to the university’s virtual
        learning environment (VLE), making use of one of its standard lesson
        structures. This was a somewhat clumsy process involving uploading
        screens and audio separately, and was restricted by the content and
        structure of the rest of the VLE’s standard layout.
     
   
  
    
    
      Figure 5 shows a prototype improved version made using Flash. In
        this version, annotations are better synchronized with the audio
        content, so that the arrows and boxes appear and disappear exactly when
        they are needed. (If you are reading this article online, you can run the complete e-Proof).
     
   
      
  
  Addressing theoretical and practical issues
  In the theoretical framework section we discussed four facets from Lin and Yang’s (2007) breakdown of proof comprehension: basic knowledge
    (relevant background procedural and conceptual knowledge), logical
    status (inferring warrants), summary (identifying critical ideas and
    subproofs) and generality (identifying what is proved). Each of these
    can be supported by e-Proofs.
  Basic knowledge can be supported in a low-level way simply by
    providing correct and fluent reading of all of the words and symbols in
    the proof. Indeed, such reading might highlight important conceptual
    information, if for example a statement like “|x - a| < δ” is read out loud as “the
    distance between x and a is less than delta”. Basic
    knowledge can also be supported by providing audio reminders of relevant
    definition and theorem statements. Reading for logical status can be
    supported by giving explicit audio explanations of implicit warrants.
    Annotations can highlight which information is being used as data for a
    particular claim, even when this is dispersed across the proof, and can
    visually link this information to the conclusion. Reading in order to
    identify critical ideas and subproofs can be supported either by
    indicating their beginnings, ends and internal structure with
    line-by-line annotations or by breaking proofs down as in the chunk
    version and providing commentary on what is achieved in each section.
    Finally, reading in order to identify what is proved can be supported by
    providing a screen with arrows indicating where the theorem premises are
    used and where the conclusion appears.
  All of this information could be provided in a lecture, but here
    the explanation is not only captured but enhanced by directing attention
    precisely and having clear visuals and audio. Low-level details are
    hidden but retrievable, navigation to a specific point of difficulty is
    straightforward, the audio can be replayed as many times as the student
    wishes and the reader can proceed at his or her own pace. Also, the
    annotations appear one at a time and do not permanently add content, so
    the integrity of the proof is preserved without clutter. Overall, the
    coordination of the static underlying proof and the dynamic annotations
    and audio mean that the thinking one needs to do to understand a proof
    is made explicit in a way that could not be achieved in a lecture or a
    book.
  Design, implementation and usage
6
  Design of individual e-Proofs
  Designing an e-Proof requires considerable intellectual work
    because of two coordinated constraints: the screen size and the length
    of each audio explanation. Making a proof fit on one screen often
    requires compression compared with what might be written on a board.
    Such compression is possible because some of the explanation that might
    ordinarily appear in a board version can be put in the audio commentary
    (“by line 3”, “this contradicts our assumption at *”, and so on). On the
    other hand, the logic of the written version needs to remain clear, and
    the audio itself is also constrained. Laurillard (2002, p.110) states:
    “If a hyperlinked clip lasts longer than thirty seconds there is a sense
    of the user having ceded control, and they revert to being the viewer,
    rather than active participant…. Ten to twenty seconds is more
    comfortable.” Coordinating these aspects, however, is easier than
    deciding on the content of the explanation and how this will relate to
    what is fully visible on the screen and what annotations should appear.
    The difficulty of constructing satisfactorily short, fixed explanations
    further convinced us of the likely inadequacy of the on-the-fly
    explanations typically given in lectures.
  Implementation
  The first author constructed eight e-Proofs for an Analysis
    course that covered
    standard content on continuity, differentiability and Riemann
    integrability and was given to a cohort of 140 students in Autumn, 2008.
    For each e-Proof she first gave out printed copies of the theorem and
    proof and invited the students to spend a few minutes reading and
    discussing these. She then showed the line-by-line and chunk versions of
    the e-Proof, playing most of the audio but sometimes inviting the
    students to confirm that they could see how a simple line worked without
    it. If appropriate, she also drew a diagram on the board as the proof
    progressed. This whole process typically took approximately 15-25
    minutes, and the students did not receive any particular instruction on
    what they should do while the e-Proof was shown. Subsequently she saw a
    number of printed copies with copious annotations, but does not know
    whether these were made during lecture time. After the lecture, the
    e-Proof was made available via the course VLE page.
  This experience of using the e-Proofs led her to two main
    observations. First, when the first e-Proof was shown, the students
    seemed somewhat daunted. We believe this indicates that the e-Proof made
    clear how much work that might go into understanding a proof. Second,
    the use of e-Proofs had a noticeable effect upon her lecturing, in that
    she made many more comments than usual about the process of
    understanding proofs. She commented on what to look for in seeking
    line-by-line links and overall structure, related this to the experience
    of watching e-Proofs and indicated that this is something a student
    should do for every proof. In doing so she stressed that this process
    should take some time, but not an impossible amount. Using e-Proofs thus
    made the process of proof comprehension an overt subject of discussion
    in the lectures.
  Usage
  The VLE collects usage data for all the posted documents and
    other types of activity, so it is possible to ascertain how much the
    e-Proofs were actually used by the students. The e-Proofs were
    collectively viewed a total of 1026 times during the course and in the
    pre-examination period (seven viewings per student on average), with
    more viewings in this latter period. This was comparable with usage of
    other online resources such as solutions to not-for-credit weekly
    problem sheets. Feedback was positive, with the vast majority of
    students indicating that they would like e-Proofs for other courses. For
    more detail on usage and feedback see Alcock (2009).
  Discussion: Pedagogical affordances and limitations
7
  What e-Proofs do not do
  e-Proofs were designed to address the problem of teaching for
    proof comprehension in large, teacher-centred undergraduate mathematics
    lectures. We have argued that in theory, they can focus attention on the
    thinking needed for syntactic proof comprehension by making explicit
    both warrants for line-by-line validity and larger-scale structure.
    However, it is important to recognize the limits on what such a resource
    can contribute to the overall learning process (the following is much
    influenced by Laurillard, 2002).
  Essentially, an e-Proof allows the lecturer to articulate their
    own understanding of a proof. We have argued that it allows them to do
    this better than they could in a lecture or a standard written
    explanation, but it is still just an explanation. The lecturer can
    attempt to anticipate likely points of difficulty, but students have no
    opportunity to articulate their own conceptions and receive feedback on
    these. In this respect, e-Proofs are considerably less sophisticated
    than what Laurillard (2002, chapter 7) calls adaptive media. In
    mathematics education, one might see this by comparing with CAA (see eg. Sangwin, 2004), which can provide extrinsic feedback by responding to
    anticipated answers in particular ways, and with dynamic geometry
    software (see eg., Hadas, Hershkowitz & Schwarz, 2000), which can
    provide intrinsic feedback by allowing the student to immediately see
    the effect of their constructions and dragging actions.
  e-Proofs are interactive, but only in the weak sense
    that the student controls the pace and sequence of the content and can
    replay parts at will. In discussing interactive media, Laurillard (2002,
    p.110) notes that “[w]ithout a clear personal goal, students will tend
    to iterate through the resource without either reflection or
    adaptation”. In this case, a student can sit in front of an e-Proof
    without thoughtfully engaging just as easily as they can sit in a
    lecture without thoughtfully engaging. In the Analysis course, e-Proofs
    were combined with other types of instruction and activity, some of
    which encouraged students to share their understanding with each other
    and then reflect upon it when the e-Proof was played or a solution was
    made available. As in any learning situation, consideration must be
    given to the student’s perception of what they are supposed to be
    learning and how the learning activities and resources are supposed to
    support that (see eg., Ramsden, 2003).
  Continuing work
8
  Research and teaching
e-Proofs are designed to support proof comprehension, and with
the support of an MSOR Network mini-project award, a research study has been
undertaken to investigate whether they actually do. This project
compared students’ comprehension of a proof after a) studying an
e-Proof; b) watching a lecture; and c) reading the proof independently.
 Roy, Alcock & Inglis (2010) report that in this first exposure to a
particular proof, the lecture led to the greatest comprehension. They
discuss possible reasons for this, which are closely related to the
limitations of e-Proofs as discussed above. This work links to the work
being carried out by the ExPOUND Project (see below), where we will be
documenting how and why students use e-Proofs, both in terms of their
detailed interaction with particular proofs and as part of their overall
study for a course. Finally, lecturers at Loughborough will be exploring
the possibility of allowing students to construct their own e-Proofs for
submission as part of an assignment in a course on Communicating
Mathematics. In this way it is hoped that e-Proofs will allow students
not just to better understand lectured proofs, but to demonstrate their
own understanding of proofs that they have studied from other sources.
ExPOUND project
  With the support of a JISC Learning and Teaching Innovation Grant, work is
    now underway to develop an open-source web-based tool called ExPOUND
    (Explaining Proofs: Offering Understanding through Notated
    Demonstrations). The tool has been designed to allow both lecturers and
    students to construct e-Proofs as illustrated in the improved prototype
    version as shown in Figure 5. The tool itself is written in Flex and
    PHP, using both rapid prototyping and agile development practices, and
    has been released under an open source license so that it can be
    installed for use at other institutions and the underlying code can be
    modified for bespoke functionality. The individual ExPOUND user will,
    however, be able to construct an e-Proof through a web browser so no
    installation will be required. The user will be able to share their
    project build files so that others can make modifications for their own
    settings, and the finalised e-Proofs will be a Flash files, allowing
    easy sharing of these learning objects via, for example, an
    institutional VLE.
  The ExPOUND team has gathered early feedback by meeting with
    lecturers interested in being able to use both the ExPOUND tool and the
    e-Proof products in their teaching practice. Early indications have been
    positive: the lecturers engaged with the team, noted potential
    limitations and suggested additional features that would be useful to
    them. Many of these suggestions have been incorporated into the initial
    tool and/or documentation. Early interest has been from mathematicians,
    but lecturers from other disciplines such as design and technology and
    chemical engineering are also beginning to express interest in using
    ExPOUND to construct learning objects for their own subject areas. The
    tool has been developed with inbuilt flexibility to allow for such
    cross-discipline use in future.
  Work is currently underway to provide an online demonstrator that
    lecturers can trial; feedback received will allow the project team to
    add enhancements for future versions of the tool. The project also aims
    to make the final e-Proofs available as resources on the projects
    website, as they are developed. Those who are interested in following
    the development of the tool or engaging with the project are encouraged
    to follow its progress online at http://www.projectexpound.org.uk/. 
  Acknowledgments
9
  The e-Proofs described here were constructed with the
    support of a Loughborough University Academic Practice Award and with
    the assistance of Lee Barnett and Keith Watling of the Department of
    Mathematical Sciences. 
  The authors thank Keith Weber and Matthew Inglis for
    valuable comments on earlier drafts of this paper.
  References
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    Weber, K. (2004). Traditional instruction in advanced mathematics
      courses: A case study of one professor’s lectures and proofs in an
      introductory real analysis course. Journal of Mathematical
      Behavior, 23, 115-133.
   
  
  
  
  
  
  
  Footnotes
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