Archive for the ‘related work’ Category

Five misunderstandings about case-study research

Sunday, October 19th, 2008

I recently read a paper by Bent Flyvbjerg in which he discusses and justifies the usefulness of case study/ case methodology in social science. I am wondering whether and how is assumptions can be applied to mathematics. I am not summarizing the paper and am not providing its application to math; but simply sketch my thoughts.

Old-fashioned definition: “Case Study. The detailed examination of a single example of a class of phenomena, a case study cannot provide reliable information about the broader class, but it may be useful in the preliminary stages of an investigation since it provides hypotheses, which may be tested systematically with a larger number of cases. (Abercrombie, Hill, & Turner, 1984, p. 34)”

Cases in mathematics:

Claim: “General, theoretical (context-independent) knowledge is not more valuable than concrete, practical (context-dependent) knowledge”.

Bent Flyvbjerg discusses the role of cases and theory in human learning and emphasises that case study (e.g. carefully chosen experiments, experiences, cases) produces the type of (concrete, practical) context-dependent knowledge that research on learning shows to be necessary to allow people to develop from rule-based beginners to virtuoso experts. In contrast, textbooks provide (general, theoretical) context-independent theories (focus on universals) and bring the students just to a beginner’s level.

(This supports our work towards context-dependent mathematical learning objects; although we have so far defined context by the logical/ narrative/ social relation of mathematical knowledge — but maybe by”social” we actually mean concrete/ individualized/ practical aspects)

We make use of cases in mathematics (and maybe should adapt mathematical learning respectively rather than solely presenting abstract/ universal theories): William Farmer one’s told me about a colleague who had to give a lecture on algebra unprepared. Consequently, when presenting a proof, he had to continuously revise his steps, wipe the board, and start over again. This incremental approach actually helped the students to really understand how mathematics is practised, i.e. that the universal and abstract theories are not invented from scratch but have to be iteratively developed based on many cases — examples, counterexamples, etc. And also Cristian Calude has recently pointed out once more that the way of doing math cannot at all be compared to the way of presenting the final results!

Generalization and Force of Example

Claim: “One can often generalize on the basis of a single case (i.e. does not necessarily need statistics/ quantitative studies), and the case study may be central to scientific development via generalization as supplement or alternative to other methods. But formal generalization is overvalued as a source of scientific development, whereas the force of example is underestimated.”

In “Mathematical Naturalism” Philip Kitcher illustrates that the development of mathematics can be seen as a stepwise process from generalizations to their symbolic substitutes. Kitcher underlines the dynamics in mathematics, i.e. the creating, revising, and dismissing of mathematical knowledge, as well as the process of abstracting experiences to gain symbolic substitutes.

So what is the value of generalization and examples in mathematics? Although finding mathematical results is based on a case-based generalization process, mathematicians are particular interested in discussing the final general, abstract, and universal structures rather than looking at the concrete objects. However, particularly in teaching examples and exercises are essential, they help teachers to guide students from theory to theory (Michael Kohlhase says examples are theory morphism, i.e. “structure-preserving mappings between two mathematical structures.”).

Claim: “The case study is useful for both generating and testing of hypotheses but is not limited to these research activities alone.”

Bent Flyvbjerg cites Eckstein, John Walton, Karl Popper, who underline that case study is a mean for testing theories (Eckstein), produces the best theories (Walton), and is ideal for generalizing using falsification (critical reflexivity) (Popper). In the paper, theory is defined in two ways …

[..] theory in its “hard” sense, that is, comprising explanation and prediction [..] theory in the “soft” sense, that is, testing propositions or hypotheses” [..]

See wikipedia definition of theory, mathematical theory and list of first-order theories. See also “A shorter model theory” by Wilfrid Hodges (1997).

“In mathematical logic, a theory is a set of sentences in a formal language. One way to specify a theory is to define a set of axioms. The theory can be taken to include just those axioms, or their logical or provable consequences, as desired.”

“A syntactically consistent theory is a theory from which not every sentence in the underlying language can be proved.”

“A satisfiable theory is a theory that has a model. This means there is a structure M that satisfies every sentence in the theory. “

Falsification is widely used to test and, if needed, refute mathematical theories: “If just one observation does not fit with the proposition, it is considered not valid generally and must therefore be either revised or rejected.” (cf. Flyvbjerg).

Claim: “The generalizability of case studies can be increased by the strategic selection of cases. When the objective is to achieve the greatest possible amount of information on a given problem or phenomenon, a representative case or a random sample may not be the most appropriate strategy. This is because the typical or average case is often not the richest in information. Atypical or extreme cases often reveal more information because they activate more actors and more basic mechanisms in the situation studied.”

This takes on the discussion by Kerber et. al., which have addressed the typicality of examples. However, in mathematics (in particular teaching) we also make us of atypical examples, counter examples, and near-miss examples. (Note, we might want to use our study of typical examples to eventually identify atypical examples. Moreover, we might want to apply the types of cases by Flyvbjerg to mathematical examples and exercises)

Flyvberg presents several strategies for selection different cases (see figure below): Among others …

  • extreme cases: Getting a point across in an especially dramatic way, see e.g. Normen’s motivative example for management of change — Adriane 5
  • critical cases: Require experience, looking for “most likely” and “least likely” cases, i.e. cases to either clearly confirm or irrefutably falsify propositions and hypothesis
  • paradigmatic cases: Cases that highlight more general characteristics of the societies in questions; Kuhn showed that scientific paradigms cannot be expressed as rules and theories as there exists no predictive theories how predictive theory comes out; discovering paradigmatic cases requires intuition and taken-for-granted procedures
Strategies for the Selection of Samples and Cases

Strategies for the Selection of Samples and Cases

Do Case Studies Contain a Subjective Bias?

According to Flyvbjerg, it is falsification, not verification, that characterizes the case study. Moreover, the question of subjectivism and bias toward verification applies to all methods, not just to the case study.

This question also applies to mathematics. Rarely any human being is able to provide fully objective illustration, thus, also mathematical results have an individual touch and can include subjective, context-dependent parts influenced by the type of problem or personal views. In mathematics, single subjective cases do not lead to accepted and verified results. Instead we can observe a communal and peer-reviewed process within which a given proof is falsified and tested (see discussion with Cristian Calude).

Case studies often contain a substantial element of narrative. Good narratives typically approach the complexities and contradictions of real life. Accordingly, such narratives may be difficult or impossible to summarize into neat scientific formulae, general propositions, and theories.

I recommend to read pages 238-239, as Flyvberg’s illustration open a very new perspective on our work on mathematical examples (see below): “The opposite of summing up and “closing” a case study is to keep it open. [..] I tell the story in its diversity [..] I avoid linking the case with the theories [..] Instead, I relate the case to broader philosophical positions that cut across specializations. In this way, I try to leave scope for readers of different backgrounds to make different interpretations and draw diverse conclusions regarding the question of what the case is a case of. [..] Case study is a “virtual reality” [..] Students can safely be let loose in this kind of reality, which provides a useful training ground with insights into real-life practices that academic teaching often does not provide. [..]“ … maybe mathematical examples are more than theory morphisms (i.e. clear mappings between theories), maybe that have to leave room for imagination and interpretation. However, math is different to social science such as political studies or philosophy and mathematical knowledge is of a very different kind then social-science knowledge: it is abstract, well-structured, extraordinary interlinked, has a precise syntax and semantics. Well, but these characteristics make access to mathematical knowledge also so hard for novice: Maybe before being abstracted into clear structures in the human mind it has to be of a different form to be more easily understood by novice.

“One might say that the rule formulation that takes place when researchers summarize their work into theories is characteristic of the culture of research, of researchers, and of theoretical activity, but [..] something essential may be lost by this summarizing [..] “

This is indeed a problem in mathematics: When getting reading to write down their mathematical concepts, mathematicians do not fully articulate their thoughts but leave out parts that well-experienced mathematicians can fill in. However, students are lacking the observations/ experiences/ examples/ cases that experts have acquired through-out the years and have difficulties in understanding theoretic and abstract writings.

Further Reading

  • Robert Stake’s (1995): The Art of Case Study Research
  • Charles Ragin and Howard Becker’s (1992): What Is a Case?
  • Scenario-based techniques

Development, Continuity, and Connectivity of Scientific Communities

Monday, September 29th, 2008

Research by Andrea Kienle and Martin Wessner

I have been following the work by Kienle and Wessner during my analysis of related work in the area of scientific communities of practice. I want to point to the design patterns listed by the authors as I find them particularly interesting in the discussion on the future of the open knowledge society and its venues.

  • Smooth transitions between different degrees of participation: New people with new ideas should be able to join the community as easily as possible; already existing members should be able to participate over a period of time on different levels.
  • Networking of local coordinators: Local coordinators influence by their publications, lectures, and advice how other work is perceived by their fellows.
  • Rotation of meeting locations: To provide low barriers for new people living near the meeting location to enter the community.
  • International program committees: committee members distribute information about the conference locally and encourage people from their local networks to submit to the conference. International program committees may thus lead to more international group of authors.

These principles have been based on an empirical study and biometric analysis of the CSCL community as well as conceptual work by Etienne Wenger et Al.. The design principles have been applied to propose a community platform for the CSCL community. A community platform might also be potentially useful to foster the the exchange and discussion in the knowledge society.

For more detailed information see:

MILCA – A Mobile and Interactive Learning Environment on Campus

Friday, September 26th, 2008

Presentation by Kin Choon Yow (Nanyang Technological University, Singapore) at the 1st World Summit of the Open Knowledge Society, Athens, 24-26 September 2008. Track: Knowledge, Learning, Education, Learning Technologies, and eLearning for the Knowledge Society.

Current learning scenarios are not interactive. But in particular Asian students are very shy and do not dare to ask questions in the classroom. But they are more likely to engage in technologies and post their question online. So can we make use of mobile classroom scenarios? The presented system is build on two core technologies: Multimedia Messaging Service (MMS) and Live Audio Streaming. Students can follow the lecture anywhere on campus. The system is also used in classroom and particularly helpful for lecture with high numbers of participants. Students can send their questions via MMS to the lecturer, MMS questions are displayed underneath the slides, and lecturers can immediately react (real-time lecture feedback).

Evaluation Results: Students like it (some find it cool). Shy students can build up confidence to ask questions. Allow students asking questions even in large classes. Lecturers can understand better how students think and if/how they follow the course. Lecturer can adjust teaching pace immediately.

Questions: How to deal with high numbers of questions during the class? Currently, lecturer answer questions at the end of each sub-section. Some question are similar and are skipped. Do students loose much (attention) time when typing the messages? But the young generation is pretty fast. What are challenges of distance-teaching? Teacher seems to have problems to talk to a screen for several hours. Teacher loose the control and immediate feedback when teaching online, they have bigger influence in the classroom. The social experience of regularly going to university might actually be an important aspect of the learning experience.

Strict and Pragmatic OMDoc

Wednesday, September 17th, 2008

Please note I am not an expert in the discussion on strict and pragmatic OMDoc, but I want to add some notes from our last discussion that helped me understand why we need both. Below you find the current definition of both terms:

This next version of OMDoc mainly adds the notion of “strict OMDoc” to serve as a canonical, semantic core of the OMDoc functionality. The current OMDoc vocabulary is re-interpreted as “pragmatic OMDoc” via translating into strict OMDoc.

We are currently still lacking usable editors for creating and maintaining our OMDoc corpus. Consequently, our users are still typing OMDoc or using our sTeX2OMDoc workflow to create OMDoc. To facilitate the editing process, we want to provide a less strict format, i.e. pragmatic OMDoc.The strict OMDoc also introduces some conceptual changes, which radical shorten the current OMDoc vocabulary, and aims towards a rather fundamental markup of OMDoc. However, in a more traditional view, these radical changes can cause disagreements with our previous users. Consequently, for the future we will maintain pragmatic and strict OMDoc. We might even introduce further pragmatic views on OMDoc targeted towards non-mathematicians and rather practical scenarios.

For further information see the OMDoc portal.

Towards Active Documents

Wednesday, September 17th, 2008

In my last post I mentioned that KWARC has a lot of topics and implementation that can be of interest to e.g. support education in mathematics. Recent initiatives aim towards a Javascript framework for active documents.

Active documents are documents in a browser that provide semantic services based on the semantics inside the document (marked up in our Open Mathematical Document Format (OMDoc)). Below I am listing potential services we have in mind:

  • Folding of formula e.g. (a/b)+(a/c) is reduced to … + …, when clicking on the + symbol
  • Interlinking of symbols and their definitions
  • Providing a guided tour to explain a given forumla. The tour provides all definitions and explanations of symbols in the formula.
  • Search for the document’s formulae in the WWW (based on our MathWebSearch engine)
  • Unfolding of formulae based on definition: e.g. 3! is unfolded into 1*2*3
  • changing notations
  • flexible elisions (see demo)
  • proving mathematical statements

Our vision is to provide these services in a right-click menu for our semantic document format OMDoc. Currently, some of these services are available but have to be hard-wired in the XHTML. However, by making use of the maction-element we are now able to provide more dynamic and interactive services.

Besides the implementation of the framework, I am interested in evaluating our new service and am looking for any feedback and ideas. The questions below focus on eLearning scenario, however our service is not limited to this area but can also be applied to e.g. scientific use cases.

  • Are our features helpful for mathematical education?
  • What impact do we expect them to have on users?
  • How can we measure this impact?
  • Which additional features are need to make our service usable and intuitive for the eLearning community?
  • Are these features of interest to the math education community? How can we increase their acceptance/ usage of our work?

Interactive exercise in panta rhei

Thursday, September 11th, 2008

Talking to Hans Cuypers, Einhoven University of Technology, about the efforts of integrating the interactive exercise web service into panta rhei at the 4th European Workshop on Mathematical & Science eContents.

In particular, I want to use it to analyse different problem solving strategies of students. For this we need to write several alternative strategies for the service and implement a tracking (Jan Knopper has started this for MathDox) that allows to re-produce the steps of the students. Additionally, we can store the time and score for the exercise. This could be an interesting student project.

Alternatively, Hans Cuypers offered to link to their server and make use of their existing strategies and exercises (most of them in Dutch). This could potentially allow a better preparation of students (than our current precourse quizzes) but is less helpful for our analysis on mathematical (problem solving) practices.

Message from CICM: Tagging and Annotating Proofs

Monday, July 28th, 2008

See MathUI paper. Annotea-Extension for Proof Documents.

Message from CICM: MathEdit – an Alternative to the Sentido Formulae Editor?

Sunday, July 27th, 2008

See MathUI submission

Message from CICM: Notation and Frequency of Symbols

Sunday, July 27th, 2008

At CICM 2008 (Workshop DML), Stephen Watt presented his work on analyzing the frequency of symbols, that would be an interesting infrastructure for further cop-based analysis.
See Michael’s blog and the DML Proceedings.

Another talk (Workshop MathUI) was on his handwriting recognition of mathematical notations: Presenting his Representation Approach. See paper

The challenge is that there is no fixed dictionary. But maybe CoPs provide some restrictions of potential parsing results? Or is frequency a better approach?

Message from CICM: iMath – Case Study on Mathematical Notation Writing

Sunday, July 27th, 2008

Marc Wagner implemented a plugin for TeXmacs which tracks a user writing and modifying a document. This was done to gain intuitions for extending is Plato editor (identifying the linguistic phenomena). And interesting aspect are that the process of writing of notations is also a practice, not just the selection of a notation. Another aspect is the level of formality users choose to solve their tasks. An analysis of the solutions might be an interesting case study for CoPs.

  • Most modification where due to notations errors (so automatic verification would be very helpful).
  • Sentences fragments where classified (linguistic ontology to deal with linguistic proofs)
  • Pointed out practice for “concluding step”.
  • Pointed out practice for “justifying” steps. (partly very hard to parse automatically: specific science or natural language)

Plan for the future: Additional components for the “ideal mathematical assistance system”. Among others

  • Linguistic Ontology for concepts, types, theory structures.
  • Dynamic Adaptation of Notations (Change Management).
  • Context Memory???.

See paper at MathUI 2008