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State of the Art of Adaptivity in E-Learning Platforms.

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  • University of Applied Sciences Upper Austria, Hagenberg

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Adaptivity has been an important research topic during the past two decades, especially in the field of e-learning. This paper deals with the question of whether and to what extent adaptiv- ity is actually being used in e-learning systems. It describes the state of the art of adaptivity features and gives an overview on the most frequently used learning management systems (LMSs) as well as on a number of research projects and sys- tems providing adaptivity.
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State of the Art of Adaptivity in E-Learning Platforms
David Hauger and Mirjam K¨
ock
Institute for Information Processing and Microprocessor Technology
Johannes Kepler University, Linz
Abstract
Adaptivity has been an important research topic
during the past two decades, especially in the
field of e-learning. This paper deals with the
question of whether and to what extent adaptiv-
ity is actually being used in e-learning systems. It
describes the state of the art of adaptivity features
and gives an overview on the most frequently
used learning management systems (LMSs) as
well as on a number of research projects and sys-
tems providing adaptivity.
1 Introduction
Adaptive Hypermedia (AH) has been explored and re-
searched for several years now. In 1996 Brusilovsky
claimed that [Brusilovsky, 1996b, p. 1]
AH systems can be useful in any application
area where the system is expected to be used by
people with different goals and knowledge and
where the hyperspace is reasonably big. Users
with different goals and knowledge may be inter-
ested in different pieces of information presented
on a hypermedia page and may use different links
for navigation.
In the same paper he pointed out that adaptivity can be
especially helpful in education and listed some first ap-
proaches to educational AH systems. There has been a lot
of work and research in adaptive educational hypermedia
in the intervening years, evidenced by the number of pub-
lications and dedicated events.
This paper examines the extent to which adaptivity is
employed today in widely used e-learning systems. The
rest of the paper is structured as follows: Section 2 deals
with the question whether and how adaptivity can enhance
e-learning. Moreover, it introduces several adaptation tech-
niques. Section 3 presents a list of popular LMSs as well
as an overview on some systems already providing adaptiv-
ity features. The paper is concluded with a summary and
discussion of the findings.
2 Adaptivity in E-Learning
This section deals with adaptivity in e-learning systems and
explains why and how adaptivity is able to improve the
quality of e-learning environments.
2.1 Why Can Adaptivity Enhance E-Learning?
According to [Brusilovsky, 1996a]adaptivity is of particu-
lar importance in the field of e-learning for two main rea-
sons. First, a learning system might be used by learners
differing in their goals, learning styles, preferences, know-
ledge and background. Moreover, the profile of a single
learner changes (e.g. the knowledge increases as an effect
of learning). Second, the system can help the learner to
navigate through a course by providing user-specific (not
necessarily linear) paths.
Taking care of these differences, the system is able to
provide personalized access to the content (fitting the indi-
vidual user’s needs). The fact that the decisions on what is
presented are based on the user’s profile (e.g. goals, know-
ledge) allows taking care of a single user. This compensates
for one significant problem of common e-learning systems
that provide the same view of the information for all learn-
ers.
2.2 How Can Adaptivity Enhance E-Learning?
There are several different ways to categorize adaptivity
features. [Beaumont and Brusilovsky, 1995]distinguish
between adaptation on content level (adaptive presentation
support) and on link level (adaptive navigation support).
Adaptive presentation support Adaptive presentation
support describes the presented content as an assembly of
fragments. Depending on how these fragments are put to-
gether [Beaumont and Brusilovsky, 1995]divide adaptive
presentation support into “conditional presentation” ([Fi-
scher et al., 1990]), the “stretchtext” technique ([Boyle and
Encarnacion, 1994],[Kobsa et al., 1994]) and the “frame-
based” technique (used in HYPADAPTER [B¨
ocker et al.,
1990]and EPIAIM [De Rosis et al., 1993]).
[Henze, 2000]adds page or page fragment variants as
another adaptation technique which is – although similar to
the frame-based technique – a more general approach.
[Brusilovsky, 1996b]differentiates between adaptation
techniques (implementation level) and adaptation methods
(conceptual level). [Brusilovsky, 1996b]lists the following
methods for adaptive presentation support:
Additional explanations: Displays the parts of a doc-
ument matching the user’s knowledge or goal (used
in MetaDoc [Boyle and Encarnacion, 1994], KN-
AHS [Kobsa et al., 1994], ITEM/IP [Brusilovsky,
1992], EPIAIM and ANATOM-TUTOR [Beaumont,
1994]).
Prerequisite explanations: If prerequisites for a con-
cept are not sufficiently known, the corresponding in-
formation is inserted by the system (used in Lisp-
Critic [Fischer et al., 1990]and C-book [Kay and
Kummerfeld, 1994]).
Comparative explanations: Emphasizes similarities
between the currently displayed concept and known
ones (used in (ITEM/IP, Lisp-Critic and C-book).
Explanation variants: In some cases displaying or
hiding parts of information is not sufficient which
leads to creating different variants of a piece of in-
formation and presenting the best fitting one (used
in ANATOM-TUTOR, Lisp-Critic, HYPADAPTER,
ORIMUHS [Encarnac¸˜
ao, 1995], SYPROS [Gon-
schorek and Herzog, 1995]and WING-MIT [Kim,
1995]).
Sorting: The fragments of information are sorted ac-
cording to their relevance for the user (used in HYP-
ADAPTER and EPIAIM).
Adaptive navigation support Adaptive navigation sup-
port deals with all the possibilities of modifying visual
links enabling navigation (e.g. by reordering, hiding or an-
notation).
As for adaptive presentation support [Henze, 2000]
defines various methods for adaptive navigation support
(based on [Brusilovsky, 1996b]):
Direct guidance: The user is provided a sequential
path through the system, either using the “next best”
strategy (guidance with a “next”-button) or “page se-
quencing or trails”, where reading sequences through
(parts of) the system are generated.
Adaptive sorting: The links of a document are sorted
according to their assumed relevance (based on previ-
ous knowledge or similarity to the current document).
Adaptive hiding: Links are hidden or disabled if the
system assumes that they are not relevant and/or dis-
tracting.
Link annotation: Links are annotated by text, colour-
ing, an icon, or dimming in order to give some extra
information to the learner.
Map annotation: The discussed annotation meth-
ods are used for adapting graphical overviews and/or
maps.
Criteria for adaptation An adaptive system may be ei-
ther concept-based or not bound to a specific concept
([Aroyo et al., 2006]). Concept-based systems use a model
of the content (the “domain model” or “content model”) to
structure the information. If the structure of the content is
relatively straightforward or the content is of small size, it
may not be necessary to develop a specific model.
Especially in the area of adaptive learning systems
concept-based architectures are more commonly used.
According to [Aroyo et al., 2006]the adaptation itself
is based on a user’s preferences (e.g. learning and cog-
nitive styles, language) as well as on assumptions about
the current user’s (knowledge) state. [Kareal and Kl´
ema,
2006]state that the presented information should adapt to
the learners’ prior knowledge and skills, learning capabil-
ities, learning preferences or styles, performance level and
knowledge state, interests, personal circumstances (loca-
tion, tempo, etc.) and motivation.
3 Overview of E-Learning Systems
The first section of this section gives an overview on pop-
ular e-learning systems. The second section of this section
provides a list of systems using the adaptivity features men-
tioned in section 2.2.
3.1 Popular E-Learning Systems
The number of e-learning systems has constantly been in-
creasing during the past years as a lot of companies, facul-
ties, universities and other institutions developed systems
for common or personal use. Therefore, it is practically
impossible to set up a complete list of e-learning systems.
The following list includes some of the systems most fre-
quently used in e-learning (mainly Learning Management
Systems (LMSs)).
.LRN [.LRN]is an open source e-learning and com-
munity building software originally developed at MIT.
Today it is supported by a worldwide consortium
of educational institutions, non-profit organisations,
some industry partners and open source developers.
.LRN is built on the top of OpenACS (Open Archi-
tecture Community System) [OpenACS]which is a
toolkit for building scalable, community-oriented web
applications.
ATutor [ATutor]is an open source system support-
ing learning and content management and specifi-
cally considering accessibility and adaptability issues.
It was first released in 2002 after two studies con-
ducted that evaluated the accessibility of learning plat-
forms to people with disabilities. Several features are
planned for the near future, including a barrier free
authoring tool and a streaming media server.
Blackboard [Blackboard]was founded in 1997 and
provides course and content management systems,
collaboration tools and a number of other services
combined in the “Academic Suite” and the “Business
Suite”. It is one of the most popular and successful
commercial e-learning systems. It can be extended
according to own needs.
Bodington [Bodington]is an open source LMS spe-
cialized on higher and further education developed by
the University of Leeds. Bodington uses the metaphor
of “buildings”, “floors”, and “rooms” to structure the
Virtual Learning Environment (VLE). The main target
is to be pedagogically flexible. In September 2006 the
University of Oxford, the University of Cambridge,
the UHI Millennium Institute and the University of
Hull announced the “Tetra Collaboration” between
Sakai and Bodington.
BSCW [BSCW](Basic Support for Cooperative
Work) is a commercial shared workspace system
mainly supporting advanced document management.
Additionally it offers group and time management fa-
cilities as well as communication features like discus-
sion boards, annotations and surveys. The project was
initiated in 1995 and is still developed by FIT (Fraun-
hofer Institute of Technology) and OrbiTeam.
CLIX [CLIX]is a commercial LMS developed by the
imc (information multimedia communication) AG. It
is available in different releases especially suitable for
several different application scenarios.Additionally
there are a couple of auxiliary features that can be
added to the basic application in order to fit the in-
dividual needs of a scenario or project.
Dokeos [Dokeos]is a quite complex e-learning and
CM system and evolved out of the LMS “Claroline”.
Most parts of the software can be downloaded for
free, whereas others are offered on a commercial ba-
sis by the like-named company. In terms of adap-
tivity Dokeos provides progress-based learning paths
(teachers may define prerequisites for items).
Ilias [Ilias]is a service-oriented open source LMS,
whose first prototype was developed within the VIR-
TUS project in 1997/1998 at the University of
Cologne. In 2000 Ilias became an open source soft-
ware. Currently, it is being developed by a collabora-
tion network of several universities and companies.
InterWise [InterWise]is a commercial conferenc-
ing and collaboration tool. It provides mainly syn-
chronous possibilities of interaction including audio
and video conferencing, desktop sharing, instant mes-
saging, whiteboard, etc. Although it is no traditional
learning platform, but more a conferencing tool, its
main focus lies on e-learning (primarily in compa-
nies). InterWise provides virtual classrooms with pos-
sibilities going further than those of usual conferenc-
ing systems, e.g. by implementing different roles and
the possibility to pose questions and receive statistics
on the answers.
Moodle [Moodle]is a very popular free Course Man-
agement System (CMS) that has its origins in the
1990ies. In 2003 the company moodle.com was
launched to provide commercial support, managed
hosting, consulting and other services. Since 2005
there is a fixed team of lead developers employed by
Moodle, in addition to a large community of develop-
ers and supporting organisations contributing source
code, ideas, etc. to the project. The general design
tries to consider pedagogical principles and learning
theories. The lesson module of Moodle also provides
different learning paths. As the user’s possible an-
swers on a question can be used as starting points for
different learning paths, some kind of “weak adaptiv-
ity” is supported (depending on the definition of adap-
tivity - as there is no user model).
The OLAT [OLAT](Online Learning And Training)
project was started in 1999 at the University of Z¨
urich.
OLAT is a free LMS that is, since 2001, officially
supported by the IT Department of the University of
Z¨
urich. In 2004 OLAT became open source.Today
further development ist still lead by the University of
Z¨
urich, commercial support for the LMS is offered by
various companies.
OpenUSS with Freestyle Learning [OpenUSS]was
developed by the University of M¨
unster (starting
in 2000). According to the website [OpenUSS]
“Freestyle Learning (FSL) and Open University Sup-
port System (OpenUSS) are specifications for Learn-
ing Content System (LCS) and Learning Management
System (LMS). They provide J2SE, J2ME and J2EE
reference implementations on those specifications”.
OpenLMS is now also collaborating with OpenUSS.
Sakai [Sakai]is a service-oriented Java-based open
source LMS developed in 2004 by the universities of
Michigan, Indiana, Stanford and the Massachusetts
Institute of Technology. They contributed their ex-
isting LMSs to the new e-learning platform. Later
other projects and partner institutions joined the Sakai
community and developed Sakai tools based on their
products (e.g. OSPortfolio, Samigo, Melete). Today
Sakai is developed by 116 cooperating organizations
and funded via a partners program.
WebCT [WebCT]was a commercial Course Manage-
ment System created in 1996 at the University of
British Columbia. In 2006 WebCT was acquired by
Blackboard [Blackboard], but it is still in use.
Unfortunately these systems provide no or just weak
adaptivity features. Although adaptivity has been a re-
search topic for about fifteen years, it is still used mainly
in research projects rather than in the most frequently used
LMSs (see table in figure 1).
3.2 Adaptive E-Learning Systems
The previous section provided a brief overview of popu-
lar, widely used e-learning systems. This section focuses
on well-known historical and modern adaptive e-learning
systems instead, which, while not as popular, have exten-
sive support for adaptivity; most of these systems provide
both adaptive presentation support and adaptive navigation
support.
AHA [AHA]is an open Adaptive Hypermedia Archi-
tecture providing adaptive content presentation based
on fragments as well as link annotation and link hid-
ing [De Bra and Calvi, 1998]. The current version is
based on AHAM (Adaptive Hypermedia Application
Model) [De Bra et al., 2002]. User Model and Adap-
tation Engine are strictly separated.
ALFANET [ALFANET](Active Learning For Adap-
tive Internet) was developed within a European project
from May 2002 to April 2005. Its architecture is
service-oriented, uses multi-agent technology and is
based on several standards [Santos et al., 2004](e.g.
IMS-LD, IMS-QTI, IMS-CP, IEEE-LOM, IMS-LIP).
ANATOM-TUTOR [Beaumont, 1994]is an adaptive
system for teaching anatomy. It can be used in three
different modes: browsing mode (without any adap-
tivity), question mode (using the user model exten-
sively to find questions and to evaluate the answers)
and hypermode (adaptive presentation and navigation
support).
AnnotatEd [Farzan and Brusilovsky, 2006]is an adap-
tive tool for annotating web pages. Based on the anno-
tations (peer review) this tool is able to provide social
navigation support. AnnotatEd can be used in combi-
nation with Knowledge Sea (see below).
CHEOPS [Negro et al., 1998]uses an internal knowl-
edge model to provide adaptivity and is implemented
as a set of CGI-BIN PERL scripts. The main informa-
tion taken into account is the history of visited pages.
Moreover, the system allows annotations on specific
pages.
ELM-ART [Weber and Brusilovsky, 2001]provides
information as an interactive adaptive textbook and
uses a combination of an overlay model and an
episodic student model to provide adaptive navigation
support, course sequencing, individualized diagno-
sis of student solutions, and example-based problem-
solving support.
EPIAIM [De Rosis et al., 1993]is used for statistics in
epidemiology and generates user-taylored messages.
The main focus of this adaptive system lies on the gen-
eration of natural language based on the experience of
a user within a certain knowledge domain.
HYPADAPTER [B¨
ocker et al., 1990]supports ex-
ploratory learning in the domain of Common Lisp and
offers adaptive presentation support as well as adap-
tive navigation support (sorting, hiding, annotating).
InterBook [InterBook],[Brusilovsky et al., 1998]is
an authoring tool for the development and delivery
of adaptive electronic textbooks that transforms plain
text to specially annotated HTML. It includes a web
server for the publication of the textbooks, stores an
individual model for each user and provides adaptive
guidance, adaptive navigation support, and adaptive
help.
ITEM/IP [Brusilovsky, 1992](Intelligent Tutor, Envi-
ronment and Manual for Introductory Programming)
supports a course on introductory programming based
on the minilanguage Turingal. “The mini-language
serves as a tool in mastering the main concepts of pro-
gramming, programming languages’ structures and
skills in program design and debugging. ITEM/IP
consists of several interacting components providing
support for the different phases of the learning pro-
cess: the pedagogical module (enhancing the choice
of teaching operations), the programming laboratory
(enabling students to work independently) and the in-
formation kernel (including all factual knowledge).
iWeaver [Wolf, 2003]is a PhD project designed to
provide an adaptive, flexible learning environment for
the Java programming language. The system creates
a learner profile by assessing learning styles with the
help of a range of multiple choice questions when the
user first enters. Later users receive personalized re-
commendations and an individual view of the avail-
able learning tools. iWeaver combines adaptive navi-
gation and adaptive content presentation techniques.
KN-AHS [Kobsa et al., 1994]is an adaptive hyper-
text client for the user modeling system BGP-MS. It
provides automatic adaptation of hypertext to a user’s
state of domain knowledge. KN-AHS draws assump-
tions about the user’s knowledge by an initial inter-
view and some of the hypertext actions the user per-
forms. When a new concept is introduced, its pre-
sentation is adapted to the user’s familiarity with it,
e.g. by offering additional explanations after having
retrieved the respective information from the related
user model.
KnowledgeSea II [Brusilovsky et al., 2006]is a sys-
tem for personalized information access. It offers var-
ious methods of accessing information, including two-
level visualization, hypertext browsing, recommenda-
tion and social search. Personalization is provided
by social navigation support which is an approach
for browsing-based and recommendation-based infor-
mation access. KnowledgeSea II includes an adap-
tive search facility combining a common vector search
engine and social navigation. By that every user
may benefit from the whole community’s knowledge;
search results are adapted to the user based on the his-
tory of activities.
KnowledgeTree [Brusilovsky, 2004]is a distributed
architecture for adaptive e-learning based on the re-
use of intelligent educational activities. It combines
learning content and learning support devices and pre-
sumes the existence of at least four kinds of communi-
cating servers: activity servers, value-adding servers,
learning portals (e.g. KnowledgeSea) and student
modeling servers.
MetaDoc [Boyle and Encarnacion, 1994]introduces
an adaptive presentation technique based on stretch-
text. It handles nodes as stretchtext pages and presents
a requested page collapsing all extensions not relevant
and uncollapsing all extensions relevant for the user.
METOD [METOD](MetaTool for Educational Plat-
form Design) is a European Union funded project ba-
sically aiming at creating a general paradigm for edu-
cational platform development. Part of the project’s
results is MetaTool that allows creating METOD
projects storing various kinds of content and (meta)
information, e.g. topics, student types, learning styles,
exercises and learning paths. The projects can then
be exported to various Content Management Systems
that have to support a specific METOD plugin in order
to provide adaptive learning.
NetCoach [NetCoach]is a further development of
ELM-ART containing an own authoring system that
allows the development of adaptive courses. Gener-
ally all material belonging to a course is organized
in a tree structure and can be freely browsed by the
learner. Additionally, the system offers personaliza-
tion of courses by adaptive curriculum sequencing and
adaptive link annotation.
SQL-Tutor [Mitrovic and Ohlsson, 1999]combines
Intelligent Tutoring and Adaptive Hypermedia in a
constraint-based architecture. It provides support for
university-level students learning SQL and consists of
an interface, a pedagogical module and a student mo-
deling unit analyzing students’ answers.
4 Discussion and Conclusion
The previous section shows that over the past two decades
a lot of effort was put into exploring and researching the
benefits of adaptivity in e-learning. Therefore a large num-
ber of research projects and systems (including the ones
mentioned in section 3.2) already uses adaptivity.
Unfortunately, none of these systems is already being
used by a large and worldwide community outside the
research area. Most of the popular e-learning platforms
have not yet taken advantage of adaptivity, possibly be-
cause the expected profit does not yet justify the high effort
of implementing and authoring adaptive courses. More-
over, most adaptive systems do not support e-learning stan-
dards [Paramythis and Loidl-Reisinger, 2004].
Table 1 presents an overview on features supported by
some representative systems (listed in section 3).
Within this table we may identify two groups of systems.
The first group – systems mentioned in section 3.1 – sup-
ports a lot of “standard features” a learning platform is ex-
pected to include, but as already mentioned they do not
provide adaptivity features. The second group – systems
mentioned in section 3.2 – provides these features, but as
many of the “standard features” are missing, they are rather
not suitable for common e-learning scenarios.
The next step in order to make the knowledge and ex-
perience gained in research projects on adaptivity available
Figure 1: Features of e-learning systems
to a large community of learners would be their combina-
tion with commonly required features. As research projects
usually neither aim at the implementation of already widely
used features nor have the capacities and resources to re-
develop them, a better approach would be the transfer of
achievements in the field of adaptivity into the development
of the large and most frequently used systems.
Acknowledgements
The work reported in this paper has been partially funded
by the Socrates Minerva “Adaptive Learning Spaces”
(ALS) project (229714-CP-1-2006-1-NL-MPP). For infor-
mation on the ALS project please refer to the project’s web
site: http://www.als-project.org.
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... Sakai is a popular open-source VLE which came about as a result of the merger of different universities' VLEs. It was developed in 2004 by the Universities of Stanford, Indiana, and Michigan and the Massachusetts Institute of Technology (Farmer & Dolphin, 2005;Hauger & Köck, 2007). These higher education institutions contributed their proprietary LMS for the development of Sakai. ...
... These higher education institutions contributed their proprietary LMS for the development of Sakai. The collaboration resulted in an alliance known as the Sakai community (Farmer & Dolphin, 2005; Sakai, n.d) that now comprises of more than 116 organisations that are responsible for the development and management of the project (Hauger & Köck, 2007). Similar to other VLEs, Sakai comprises of a range of tools (for collaborative, instructional, assessment, etc.) which are integrated to provide a holistic teaching and learning platform (Sakai, n.d). ...
... Different studies have been conducted to investigate the pros and cons of using this system. Graf & List (2005) ranked Sakai as a low adaptive LMS as it only offers the basic features (such as email, content repository, quizzes, forum, and chat) of an LMS (Hauger & Köck, 2007). However, Kumar et al. (2011) rated Sakai as one of the best LMSs that featured more capabilities and tools in three categories -learning tools, support tools, and technical specification tools. ...
Chapter
The integration of ICT in the education system has led to the continuous development and adoption of technology-enhanced learning (TEL) platforms such as the virtual learning environment (VLE) to facilitate and activate TEL practices in higher education institutions. The use of VLE such as MOODLE and Blackboard is proliferating; however, the experience of users in determining the relevance of VLE in enhancing teaching and learning has been identified to be an important factor in the successful use of VLEs. This chapter employed a quantitative method to examine students' experience in using VLE at the University of KwaZulu-Natal. The chapter also presents the result of the investigation into the influence of students' computer self-efficacy on their perceived ease of use, usefulness, and attitudes towards the use of VLE. The results of this study show that students believe that VLE enhances their learning. Furthermore, the results show that self-efficacy has a weak influence on students' perceived ease of use, perceived usefulness, and attitudes towards the use of VLE.
... CS development according to [4] must consider students' learning abilities, background, and motivation. Even for certain students, the requirements can change according to their increased knowledge due to learning. ...
... Several illustrations of adaptive systems exist. Adaptivity in the area of Human-Computer Interaction (HCI) involves adjusting a system, a graphical user interface, or content to meet a user's requirements (Brusilovsky, 2001;Hauger & Köck, 2007;Klašnja-Milićević, Ivanović, & Nanopoulos, 2015). Learning strategies can be matched and adapted to the learning styles and abilities of students. ...
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Aim/Purpose: Effective e-learning systems need to incorporate student characteristics such as learning style and knowledge level in order to provide a more personalized and adaptive learning experience. However, there is a need to investigate how and when to provide adaptivity based on student characteristics, and more importantly, to evaluate its value in learning enhancement. This study aims to bridge that gap by examining the effect of different modes of learning material adaptation and their sequences to the learning style and knowledge level of students in e-learning systems. Background: E-learning systems aim to provide acceptability and interactivity between students, instructors, and learning content anytime and anywhere. However, traditional systems are typically designed for generic students irrespective of individual requirements. Successful e-learning systems usually consider student characteristics such as learning style and knowledge level to provide more personalized and adaptive student-system interaction. Methodology: A controlled experiment was conducted in a learning context with 174 subjects to evaluate the learning effectiveness of adaptivity in e-learning systems. Contribution: The main contributions of the paper are threefold. First, a novel adaptive approach is proposed based on a specific learning style model and knowledge level. Second, the approach is implemented in an e-learning system to teach computer security, the application domain. Third, a rigorous experimental evaluation of the learning effect of the adaptive approach is offered. Findings: The results indicate that adaptation according to the combination of learning style and knowledge level produces significantly better learning gains, both in the short-term and medium-term, than adaptation according to either trait individually. Recommendations for Practitioners: Practitioners should consider the combination of learning style and knowledge level when delivering and presenting learning material to their students. Recommendation for Researchers: Researchers should consider sound educational models when designing adaptive e-learning systems. Also, rigorous and carful experimental design evaluations should be taken into account. Impact on Society: Universities and e-learning industries can benefit from the proposed adaptive approach and the findings in designing and developing more personalized and adaptive e-learning systems. The incorporation of student characteristics, especially learning style and knowledge level, may be used to enhance learning. Future Research: The experiment might be duplicated with a focus on longer-term learning gains by including more subjects and more learning resources. Also, the study might be expanded to application domains other than computer security. Moreover, other variables such as student satisfaction, motivation, and affective state might be explored to further the understanding of the effect of adaptivity on learning gains.
... There have been many attempts by researchers in this field to state the current status of personalized e-learning environment from different perspectives. For example, In [20], the researchers focused on giving an overview of the use of adaptivity in e-learning by investigating whether it has been used and the extent to which it has been used. The researchers concluded that the majority of e-learning systems are not providing adaptivity features. ...
Chapter
In the digital era, individualized educational services, e.g. distributed by intelligent tutoring systems, are becoming increasingly popular and important for life-long learning but also during the COVID pandemic as many universities had to switch to distance learning immediately. Intelligent tutoring systems simulate behavior and expertise of physical teachers and support learners individually. In addition to closed questions, which can be modeled simply as if-then statements or decision trees, the use of artificial intelligence enables more and more the implementation of open questions and poorly structured problems, which is of particular importance for e.g. engineering education. In order to make the learning experience authentic, it is important to understand the learners as individuals and to confront them with learning content and in-depth knowledge tailored to their needs and skills. If, e.g., a formative assessment shows that a certain content has not yet been internalized, the tutoring system must detect this and react accordingly. Since this largely corresponds to mass customizing the teaching process, the following article frames digital education with focus on intelligent tutoring systems in context with mass customization. For cracking the code of mass customizing digital education, the three mass customization key competences solution space development, robust process design as well as choice navigation are taken as reference to set up digital educational content.
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There have been many digital advancements that have helped facilitate digital transformation, such as the web's transformation. Many organisations, large and small, have recognised the power of the par-ticipatory web to improve productivity and efficiency. However, until recently, it has had little focus in the business and management literature in facilitating sustainable business-to-business (B2B) activities such as remote work practices. Two interrelated functions of business, operations, and marketing have been mapped against three dimensions of sustainability to show how these interrelated functions are related to the three dimensions of sustainability. For that reason, the research shows that with big data and social media analytics integrated into a participatory web environment, B2B companies are able to be profitable and stay sustainable by using their organisational and marketing operations and services strategically, whether it be internally or externally with other organisations.
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Valid measures of student motivation can inform the design of learning environments to engage students and maximize learning gains. This study validates a measure of student motivation, the Reduced Instructional Materials Motivation Survey (RIMMS), with a sample of Chinese middle school students using an adaptive learning system in math. Participants were 429 students from 21 provinces in China. Their ages ranged from 14 to 17 years old, and most were in 9th grade. A confirmatory factor analysis (CFA) validated the RIMMS in this context by demonstrating that RIMMS responses retained the intended four-factor structure: attention, relevance, confidence, and satisfaction. To illustrate the utility of measuring student motivation, this study identifies factors of motivation that are strongest for specific student subgroups. Students who expected to attend elite high schools rated the adaptive learning system higher on all four RIMMS motivation factors compared to students who did not expect to attend elite high schools. Lower parental education levels were associated with higher ratings on three RIMMS factors. This study contributes to the field’s understanding of student motivation in adaptive learning settings.
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Adaptive hypermedia is a new direction of research within the area of adaptive and user model-based interfaces. Adaptive hypermedia (AH) systems build a model of the individual user and apply it for adaptation to that user, for example, to adapt the content of a hypermedia page to the user's knowledge and goals, or to suggest the most relevant links to follow. AH systems are used now in several application areas where the hyperspace is reasonably large and where a hypermedia application is expected to be used by individuals with different goals, knowledge and backgrounds. This paper is a review of existing work on adaptive hypermedia. The paper is centered around a set of identified methods and techniques of AH. It introduces several dimensions of classification of AH systems, methods and techniques and describes the most important of them.
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Many Web-based educational applications are expected to be used by very different groups of users without the assistance of a human teacher. Accordingly there is a need for systems which can adapt to users with very different backgrounds, prior knowledge of the subject and learning goals. An electronic textbook is one of the most prominent varieties of Web-based educational systems. In this paper we describe an approach for developing adaptive textbooks and present InterBook—an authoring tool based on this approach which simplifies the development of adaptive electronic textbooks on the Web.
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This paper presents KnowledgeTree, an architecture for adaptive E-Learning based on distributed reusable intelligent learning activities. The goal of KnowledgeTree is to bridge the gap between the currently popular approach to Web-based education, which is centered on learning management systems vs. the powerful but underused technologies in intelligent tutoring and adaptive hypermedia. This integrative architecture attempts to address both the component-based assembly of adaptive systems and teacher-level reusability.
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Hypermedia applications generate comprehension and orientation problems due to their rich link structure. Adaptive hypermedia tries to alleviate these problems by ensuring that the links that are offered and the content of the information pages are adapted to each individual user. This is done by maintaining a user model. Most adaptive hypermedia systems are aimed at one specific application. They provide an engine for maintaining the user model and for adapting content and link structure. They use a fixed screen layout that may include windows (HTML frames) for an annotated table of contents, an overview of known or missing knowledge, etc. Such systems are typically closed and difficult to reuse for very different applications.
Conference Paper
Many Web-based educational applications are expected to be used by very different groups of users without the assistance of a human teacher. Accordingly there is a need for systems which can adapt to users with very different backgrounds, prior knowledge of the subject and learning goals. An electronic textbook is one of the most prominent varieties of Web-based educational systems. In this paper we describe an approach for developing adaptive electronic textbooks and present InterBook - an authoring tool based on this approach which simplifies the development of adaptive electronic textbooks on the Web.
Conference Paper
Adaptive hypermedia is a new direction of research within the area of adaptive and user model-based interfaces. The goal of this paper is to present the ideas and the state of the art of adaptive hypermedia, and to discuss the application of this ideas into education. Basing on their own experience, the authors talk about current state and prospects of adaptive educational hypermedia.