De - Constructing the e - Learning Pipeline

  1. 1. Jan Christoph Meister

    Universität Hamburg (University of Hamburg)

  2. 2. Birte Lönneker

    Universität Hamburg (University of Hamburg)

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For the ‘hard-core’ computing humanist, e-learning seems to be a non-topic.1 While foundational issues
and Humanities Computing (HC) curriculum development have been central to our debates, the technological and didactical nitty-gritty of e-learning appears to offer little
insight into questions of theoretical and conceptual
relevance. - This contribution argues to the contrary:
(1) The current form of e-learning is shaped to a significant degree by business and political interests.
(2) Consequently, some of the dominant commercial
e-learning platforms are conceptually flawed: they are implicitly based on a simplistic ‘cognitive
pipeline’-model of learning.
(3) HC can help to deconstruct simplistic e-models of learning and contribute towards a more ‘intelligent’ computational modelling of learning processes.
(4) The latter will be demonstrated by way of a practical example, the intermedial narratological e-course ‘NarrNetz’.
(1) Vested interests
The impression of e-learning as a non-inspiring ‘coal-face’ activity is partly a result of its swift appropriation by commercial software vendors. Indeed: there’s considerable money in e-learning – but where does it come from? In Europe, the EU and its member states have created various funding structures reserved for e-learning projects, notably eLearning: a programme
for the effective integration of Information and
Communication Technologies (ICT) in education and training systems in Europe which aims at the strategic proliferation of e-learning across the European school and university systems. 2
Meanwhile, the initial euphoria about e-learning –
fuelled in no small way by university administrators’ and politicians’ expectation to introduce a cheaper, less
staff-intensive way of teaching – has certainly worn off. The new buzzword is ‘blended learning’: the combination of physical classroom teaching with auxiliary e-learning. According to a survey presented in Schulmeister (2005), the vast majority of e-courses at non-virtual colleges and universities is indeed of an auxiliary (preparatory,
supplementary or remedial) nature. Schulmeister
concludes that in our present situation “E-learning ist die Reparatur am System, das wir einführen” – e-learning is the quick-fix for the BA/MA-system whose current introduction at German universities leads to a dramatic over stretching of teaching resources.
(2) The pipeline model of learning
However, not all short falls can be attributed to
context. In our own practical experience, part of the methodological and didactical problems associated with e-learning stem directly from restrictions imposed
by its platforms. One of the key functionalities of a
good e-learning platform is the personalized, dynamic
assignment of navigation options (so-called ‘content
release’) on the basis of results achieved by a user in
preceding tests. Depending on the scoring, hyperlinks may be made visible or activated, or the system may send
some additional feed-back. If the content manager
decides to use these functionalities, the course content must allow for tests and parallel navigation paths. Under
these conditions, this kind of interactivity can be
hard-wired into the course by the content developer who uses system provided templates for content and test
modules (questionnaires, multiple-choice etc.) and
combines these with logical or quantitative operators that specify navigation rules.
To understand the conceptual premises built into
commercial e-learning platforms (also known as LMS = Learning Management Systems), it is important to take a closer look at the kind of binary logic that drives this type of interactivity. For example, the currently still widely used WebCT Campus Edition 4 allows neither for the specification of complex (conjunctive or additive) rules of the type ‘if student X passed test 1 with > 65% and has already looked at modules 15-17, allow him/her to jump to module 22, else do Y’, nor for a logical ‘or’ in the control of a user’s navigation - fairly trivial process
control decisions which a human teacher will make on the fly in any given class-room situation.3 The impact of such concrete technological restrictions on e-learning’s current shape is severe, considering that the recently
merged WebCT and Blackboard alone account for a
joint 2/3 market share in institutional and commercial
Courses implemented on the dominant proprietary
platforms, unless their content modules are made
available in pure (non-conditional) hyperlinked form, are thus implicitly based on what we call a ‘pipeline’ model
of learning: the learning process within the system is
organised in terms of a linear accumulation of pre-defined
knowledge and skills. While the genuine dynamics of interactive learning in a real class room is the result of engagement in recursion, exploration and the adoption of a different perspective onto the same problem, systems based e-learning thus reduces much of this functionality
to mere repetition (‘repeat until you pass’), while
outsourcing true interactivity to humans (via chats,
discussion list, e-mail etc.).
Another principled problem with out-of-the-box e-
learning systems is that they are themselves not designed to learn. Whereas commercial data-base driven websites
like Amazon’s combine continuously updated user-
profiling (items bought, pages looked at, duration of visit, etc.) with probability based feed-back (‘other users who have bought item X also bought item Y’), similarly
intelligent behaviour has as yet not been implemented
in the leading commercial e-learning or course-ware
systems. While most e-learning platforms are of course able to track user behavior, they remain unable to act on process-relevant conclusions that might be drawn from this data.5
(3) Towards adaptive e-learning
So, is (e-)learning by necessity a dumber activity than shopping? Certainly not. Current AI research explores various possibilities of making it ‘feel’ more intelligent. For example, Nakano, Koyana and Inuzuka (2003) explore the role of probabilistic algorithms in the automated generation of questions; Steinemann et al (2005) as well as Yang et al (2005) look into the design principles of more sophisticated course management
systems. Providing the user with intelligent corrective feed-back is the main goal of INCOM,6 a project dedicated to developing an e-learning supported logic programming course (Le 2005, Le and Menzel 2005).
On a more general level, Moreno et al. (2005) emphasize the need for so-called ‘adaptive e-learning’ systems:
‘ Adaptive e-learning is a teaching system which adapts
the selection and the presentation of contents to the
individual learner and his learning status, his needs, his learning style, his previous knowledge and preferences.’
This topic receives particular attention in the AH
(Adaptive Hypermedia and Adaptive Web-Based
System) conference series.7 ALFANET, a project
supported by the EU-financed IST- (Information Society
Technologies) initiative, also aimed to introduce
adaptivity.8 According to the project’s self-description,
the prototype can dynamically evaluate a user’s
knowledge and then selectively assign different content
material in order to reinforce or broaden a subject.9
However, the final project report proves this to be an aim, rather than a demonstrable accomplishment.10
(4) Opening the black box
While we stake no claim to developing an
intelligent e-learning system, we do believe that an individual e-learning course can certainly be turned into a more stimulating and challenging experience through comparatively simple system adjustments – provided the system itself is not a proprietary black box. Whether such adaptations and extensions can later be implemented as generic system functionalities remains to be seen.
‘NarrNetz’ – short for ‘Narratology Network’ – uses the widely adaptable PHP/MySQL-based open source platform ILIAS11. Our project is conceptually based on a learning metaphor and an architecture that combines linear modules with explorative, highly personalised
learning experiences. Elements of NarrNetz try to
emulate the user experience of an interactive computer game – a paradigm widely expected to revolutionize the ‘look and feel’ of e-learning (Begg, Dewhurst, Mecleod
2005; Foreman/Aldrich 2005; Schaffer 2005). In
NarrNetz, the user is initially confronted with a problem
modelled on a gaming ‘quest’. However, the system and its architecture allow the combination of linear with
non-linear, systematic (deductive) with immersive
(inductive) learning methods. If learners want to like learning style. Conversely, while sections of the ‘learnflow’ follow a compulsory linear trajectory,
others may be chosen and arranged at will. Fig. 1 sketches
out the NarrNetz-learnflow which maps the user’s
navigation through the landscape of the metaphorical
quest onto the didactically desired cognitive
In our presentation we will demonstrate how
comparatively simple modifications and modular
extensions of the open-source e-learning platform
ILIAS and the integration of multi-media objects can lead to a significantly enriched, more ‘intelligent’ learning
experience. Specifically, we will discuss the following additional functionalities:
• integration of user-specific avatars with dynamically attributed ‘real-time’ properties symbolizing the user’s past progress and future navigational options at any given point in time;
• automated, personalized navigation control based on disjunctive reasoning and the concept of
multiple, functionally equivalent learning paths
rather than a pipeline-approach;
• representation of the newly acquired skills and knowledge elements in the form of a personalized
dynamic conceptual glossary; glossary entries can be cross-referenced, individually annotated and
linked to content elements of the course.
The conceptualisation and implementation of non-standard, experimental e-learning architectures
constitutes a genuine task of Humanities Computing.
As in other fields of applied humanities computing,
computing humanists are called upon to point out the conceptual shortcomings in simplistic attempts at reverse engineering human cognitive competences for the mere sake of making them ‘computable’. Learning is the most basic cognitive competence in human beings: a good enough reason not to turn a blind eye on how it is being conceptualised – technologically and ideologically.
1) HUMANIST vol. 1-19 contains 46 occurrences of the
keyword ‘e-learning’ in calls for papers, conference and publication announcements, but no genuine discussions of the topic. JLLC vol. 1-17 contains 24 rather loosely related articles, three of which are of a methodological or critical
nature: Koch 1992, Zuern 1994, McGrady 1999. The
relevant HUMANIST (vol. 1-18) and JLLC entries are
listed in – For a recent non-HC affiliated
evaluation of current e-learning methodologies see Meister 2004 (author not related).
2) On the EU e-learning initiative see
3) WebCT Campus Edition 6 claims to support the combination of multiple types of release criteria, using Boolean logic (see However, of four classes of criteria (date, member, group, grade book) only ‘grade book’ (i.e.
test results) is a dynamically instantiated variable; all
others call up absolutely, manually defined attributes. More
importantly, characteristics of a learner’s individual
navigation track cannot be specified as criteria: they are only available for manual inspection or statistical behav
ioral analysis. For details see: Designer and Instructor
Reference. WebCTTM Campus Edition 6.0. Technical Communications Department. July 16, 2005. Chapter 33: Selective Release, 773-791.
4) See
5) A word of caution: in teaching and learning, probabilistic
reasoning based system’s feed-back and navigation
control can easily become disfunctional or meet with
learners resistance. What is at stake is the very individuality
of a learning experience that may very well defy statistical
6) On INCOM, see
7) See Also see the forthcoming
special issue on Adaptive Hypermedia, Journal of Digital
8) On IST, see
9) See
10) See Barera, 2005: D66 Evaluation results, 18-21.
11) See
(All weblinks accessed 08.11.2005)
Begg, M.; Dewhurst, D.; Mcleod, H. (2005). Game-
Informed Learning: Applying Computer Game
Processes to Higher Education. Innovative. Journal of Online Education (August/September 2005:
Foreman, J., and Aldrich, C. (2005). The design of
advanced learning engines: An interview with Clark Aldrich. Innovate 1 (6).
Koch, C. (1992). Combining Connectionist and Hypertext
Techniques in the Study of Texts: A HyperNet
Approach to Literary Scholarship. LLC 1992, 7: 209-217; doi:10.1093/llc/7.4.209
Le, N.-T.; Menzel, W. (2005). Constraint-based Error Diagnosis in Logic Programming. 13th International Conference on Computers in Education 2005.
Le, N.-T. (2005): Evaluation of a Constraint-based
Error Diagnosis System for Logic Programming. 13th International Conference on Computers in
Education 2005.
McGrady, D. (1999). Making ‘wreaders’ our of students: some strategies for using technology to teach the humanities. LLC (1999), 14: 237-256; doi:10.1093/ llc/14.2.237
Meister, D.M. et al (eds.) (2004). Evaluation von
E-Learning. Zielrichtungen, methodologische Aspekte,
Zukunftsperspektiven. Münster (Waxmann) 2004.
Moreno (2005). Using Bayesian Networks in the Global Adaptive E-learning Process. Paper read at the EUNIS conference, June 21-25, University of Manchester
Nakano, T. (2003). An approach of removing errors from generated answers for E-learning. 17th Annual
Conference of the Japanese Society for AI.
Schulmeister, R. (2005). Studieren in
der Informationsgesellschaft. Vernetzt, modular,
international? (Presentation at the Campus Innovation
2005 conference, Hamburg, 20-21 September 2005.)
Shaffer, D. (2005). Epistemic games. Innovate 1 (6).
Steinemann, M.A. et al (2005). Report on the ‘Virtual
Internet and Telecommunications Laboratory
(VITELS)’ project. IAM Annual Report Academic Year 2004/2005.
Yang, F. et al (2005). A Novel Resource Recommendation System Based on Connecting to Similar E-Learners. In: Advances in Web-Based Learning – ICWL 2005. Berlin, Heidelberg: 122-130.
Zuern, J. (1999). The sense of a link: hypermedia,
hermeneutics, and the teaching of critical methodologies.
LLC 1999, 14: 43-54; doi:10.1093/llc/14.1.43
Authors’ e-mail addresses:
Jan Christoph MEISTER –

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Conference Info



Hosted at Université Paris-Sorbonne, Paris IV (Paris-Sorbonne University)

Paris, France

July 5, 2006 - July 9, 2006

151 works by 245 authors indexed

The effort to establish ADHO began in Tuebingen, at the ALLC/ACH conference in 2002: a Steering Committee was appointed at the ALLC/ACH meeting in 2004, in Gothenburg, Sweden. At the 2005 meeting in Victoria, the executive committees of the ACH and ALLC approved the governance and conference protocols and nominated their first representatives to the ‘official’ ADHO Steering Committee and various ADHO standing committees. The 2006 conference was the first Digital Humanities conference.

Conference website:

Series: ACH/ICCH (26), ACH/ALLC (18), ALLC/EADH (33), ADHO (1)

Organizers: ACH, ADHO, ALLC

  • Keywords: None
  • Language: English
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