Effective resuse and Sharing of Best Teaching Practices

Effective Reuse and Sharing
of Best Teaching Practices
AMAL AL-RASHEED,1,2
JAWAD BERRI2
1
Princess Nourah University, Riyadh, Saudi Arabia
2
King Saud University, Riyadh, Saudi Arabia
Received 28 March 2016; accepted 9 October 2016
ABSTRACT: The widespread use of computer technologies in education has reshaped the roles of instructors,
who are encouraged to innovate interactive forms of technology-supported instruction that promote participation
and collaboration. This in turn engenders new experiences of teaching that need to be gathered and capitalized as
teaching assets to be shared among communities of instructors. Among these experiences, best teaching
practices (BTPs) are instructional practices accumulated in teaching that have been proven to work well, give good
results, and can therefore be recommended as a model. Identifying and sharing best practices means duplicating
successes which help instructors learn from each other and deliver better quality teaching. This paper presents a
knowledge management framework for acquiring, coding, sharing, and reusing BTPs. To encourage instructors’
participation, the framework is based on peer scoring of BTPs, which stimulates contribution and interaction. The
framework has been implemented as a knowledge portal that allows instructors to create, store, search, and share
BTPs and to receive feedback and comments from other users, providing many useful functionalities and services
to users as individuals and communities. The paper presents also a real-life case study, lessons learned from
using the system within a community of instructors, and a system evaluation of the effectiveness of reusing BTPs
using the reuse effort and impact metrics. ß 2016 Wiley Periodicals, Inc. Comput Appl Eng Educ; View this article
online at wileyonlinelibrary.com/journal/cae; DOI 10.1002/cae.21776
Keywords: best teaching practice (BTP); knowledge management framework; knowledge sharing; community of
instructors; effectiveness
INTRODUCTION
Over the last decade, the availability of Web 2.0 technologies and
their ease of use has transformed the education landscape. These
technologies have reshaped the role of instructors, who are moving
progressively from traditional face-to-face learning toward more
interactive forms of instruction that promote participation and
collaboration [1,2]. This transition requires stakeholders to use the
richness of internal and external knowledge sources to feed the
learning process [3] while instructors must translate their expertise
into e-courses, integrating their knowledge and relevant technol-
ogies to produce intuitive learning activities that will satisfy
learners’ needs in terms of information, entertainment, and social
networking [4]. In this environment, instructors must update their
knowledge and skills to qualify and to succeed in teaching. They
must also adapt to other changes, accommodating such factors as
rapid technological development, faculty shortages, rising student
expectations, reduced funding for educational programs, and
increasing professional development demands [5]. In this new
landscape, where their daily schedule entails countless duties, it
becomes increasingly challenging to find the necessary time for
their own ongoing education. Part of this challenge is how best to
utilize the extensive teaching-related knowledge, experience and
expertise jointly accumulated by instructors over the years [6].
Instructors’ expertise in teaching a specific subject is the
accumulation of teaching experiences gained through practice,
consisting of know-what and know-how about teaching the subject
in question. The “know-what” is the requisite knowledge of course
content that must be transmitted to learners, including the
concepts, competencies, and skills to be grasped and mastered.
The “know-how” is not transmitted to learners but consists in the
methods and strategies for delivering knowledge, including
pedagogical methods, best practices, and appropriate use of
available technologies. Most e-learning and technology-enhanced
learning initiatives have focused on encoding know-what
knowledge while very little attention has been paid to the
know-how component of instructors’ expertise. To effectively
support the design, development, and delivery of learning in
educational institutions, knowledge sources need to be fully
integrated within technology-enhanced learning architectures [7].
Yet in many cases, the learning management systems, authoring
Correspondence to J. Berri (jberri@ksu.edu.sa).
© 2016 Wiley Periodicals, Inc.
1

software, social networking tools, and other education-related
software tools have been developed to facilitate the articulation
and transmission of course content to learners but unfortunately
do not enable instructors to express and communicate their
methods of teaching and knowledge delivery. In our view,
the latter constitute a valuable asset for innovation in learning
processes and are central to the successful integration of an
instructor’s intelligence in teaching practice, knowledge sources
and web technologies.
An efficient, comfortable, intuitive, and attractive learning
environment saves learners time and effort in acquiring
knowledge. For that reason, it is important to develop methods
and tools that can capture the know-how of instructors, so
enhancing the quality of education by enabling instructors to
exchange and share their teaching experiences as implemented in
practice and to report their impact on course delivery. In this
research, we address the following research question: “How might
instructor communities more effectively identify, share, and value
their teaching expertise within a framework that integrates
knowledge sources and web technologies?” To address this
question, we have developed a knowledge management (KM)
framework that allows instructors to share their teaching know-
how. More specifically, the framework targets best teaching
practices (BTPs)—the archetypal items of know-how that an
instructor develops while teaching. These BTPs can be understood
as heuristics, acquired by instructors through experience and
practice. Generally, best practices are individual; they have been
applied many times in teaching and are known to work well; they
give good results; and for all those reasons, they are recommended
as a model [8,9]. Our framework supports the acquisition,
representation, coding, and sharing of BTPs, providing instructors
with a web portal coupled with a Knowledge Management System
(KMS) to articulate their expertise. We anticipate that the
framework will support instructors in delivering quality teaching,
as they will be able to embed these best practices in their e-courses.
It is also expected that the framework will provide a platform for
specialized communities of instructors, fostering collaboration
and exchange of experiences.
The paper is organized as follows. In Literature Review
section, we review previous research relating to knowledge
management in higher education. Framework Design section
describes the framework design, and in Knowledge Management
Framework section, we propose a KM framework that allows
instructors to articulate their teaching expertise. System Imple-
mentation section describes the implementation of the framework
as a web-based system. Case Study section illustrates the use
of the system by means of a case study and discusses issues
arising. The metrics used to measure the cost and effectiveness
of BTPs are set out in BTP Quality Metrics section, and System
Experimentation section reports the results obtained from
experimentation with a set of BTPs in the system. Discussion
section discusses issues related to the design and implementation
of the system. The final section presents conclusions and some
directions for future research.
LITERATURE REVIEW
The Importance of KM for Modern Instruction
Educational institutions need to be aware of how to manage the
processes associated with the creation of their knowledge assets
and to realize the value of their intellectual capital for their
ongoing role in society. At present, these institutions engage
in significant levels of knowledge production and it is vital to
manage efficiently this knowledge for further advances. To this
end, universities and academic staff must realize and respond to
their changing role in a knowledge-based society [10]. In practice,
most academic staff are by now engaged in KM at some level
as managers of their own knowledge. As academics tend to give
long service to a university, any decision to leave can have an
adverse effect on the school and faculty and ultimately on the
institution, especially if the academic attracts students as a known
expert within a specific domain.
This raises real issues regarding the significance of
intellectual capital (particularly in the academic setting) and the
efficient use of KM standards to address this challenge [11,12].
New technologies have shaped a new information era that requires
more of university instructors in relation to personal KM [13].
Where KM tools are applied efficiently, they can facilitate better
decision-making capacity, an accelerated product development
cycle (e.g., curriculum development and research), enhanced
academic and administrative services, and reduced expenses [14].
In a recent study, Qia [15] identified three methods for
individual KM among university instructors. The first of these is to
build a knowledge communication platform to collect and manage
teachers’ knowledge, both explicit and tacit. A second method is to
establish a comprehensive knowledge base for the management
and use of collected knowledge resources. A final method involves
drawing a knowledge map of the university. The knowledge map
is a communication network that aims to help instructors to
make full use of knowledge resources, preventing repetition in the
production of knowledge and saving search time. It can also help
instructors to find the knowledge they need quickly, helping
them to solve problems related to teaching and research.
Many authors have highlighted the potential benefits of KM
for university instructors: making instructors more effective and
efficient knowledge processors [10], enhancing instructors’ devel-
opment efforts [16,17], achieving efficiencies in saving and
searching instructors’ own personal knowledge [18], facilitating
access to published knowledge sources within the academic
community [10], and increasing the overall quality of teaching
[16,19].As afinalpoint,KM canenableuniversities to addressissues
related to the utilization of intellectual capital in providing lifelong
learning opportunities [16], enhancing the quality and capability of
research [17], and speeding up innovation capability [20].
Knowledge Management Systems (KMS)
KMSs are “special type of information systems that supports
activities related to the acquisition, generation, codification, storage,
transfer, retrieval, and reuse of knowledge within organiza-
tions” [21]. The main purpose of a KMS is to support knowledge
processes. Many forms of KMSs have been applied in educational
institutions to improve the performance of instruction [22].
The evolution of information and communication technolo-
gies (ICT) in the past decade has had a significant positive effect
on KMSs that may prove important in addressing current
difficulties in sharing, transferring, and disseminating knowledge
[22]. In the context of higher education, recent developments
in ICT enable faculty to create and share high quality multimedia
resources by means of web-based knowledge-sharing systems,
and KM has become as essential in higher education as in the
corporate sector.
2 AL-RASHEED AND BERRI

The use of KM tools and technologies has been widely
discussed [23–26]. Based on the various classifications used by
these authors, the most common categories relating to KM support
for academic staff in higher education institutions are: knowledge
portals, intranet, content management systems (CMS), document
management systems (DMS), database management systems
(DBMS), data mining tools, communities of practice (CoP),
collaboration systems (Groupware), Web 2.0 or social computing
tools, and knowledge maps. In the literature, a number of research
projects have developed KMSs for managing instructors’
experience. A summary of these projects and the ICT tools they
used are listed in Table 1.
The literature on managing instructors’ experience in
universities showed many research gaps. First, most existing
research have investigated KM in education from the point of view
of experts or even outsiders; only few studies have investigated
instructors as end users of KM resources. Second, the focus in
recent studies has been on knowledge sharing among instructors,
with few studies of knowledge creation. Third, only few projects
have developed KMSs for managing university instructors’
teaching experiences. These are Web-based projects that have
deployed the concept of KM rather narrowly in relation to teaching
one or a small number of subjects, using a traditional survey
method to make tacit knowledge explicit. Fourth, while research
has been conducted to promote and develop good KM models
through individual workers, there have been fewer attempts to
support collaborative KM that facilitates communication, collab-
oration, and coordination among communities of instructors.
Finally, because of the growth of content in knowledge
repositories, it is very difficult to acquire target knowledge.
Most searches return a large number of knowledge objects,
making it difficult for users to make a decision about the most
appropriate to their needs [38,39]. By providing the means of
evaluating knowledge, assessing its quality, and recommending
the qualified experience, systems can be expected to significantly
improve user satisfaction and to leverage the quality of instruction.
FRAMEWORK DESIGN
To ensure that all requirements are fulfilled by the framework, it is
essential to use a design methodology for easy management of
design steps and to enable testing and validation of the design and
evaluation of its quality. Authors from different disciplines have
stressed the importance of design in the development of systems
and have proposed a set of design methods, principles, and
guidelines [40–42]. The objective of any such design is to develop
a representation of the system that encompasses stakeholder
requirements and business needs while also taking account of any
technical considerations for implementation [40]. Figure 1 shows
an overview of the design process.
To begin, the requirements defining stakeholder and business
needs were collected through brainstorming sessions and were
then analyzed, classified, and formulated. The findings confirmed
the relevance of sharing instructors’ expertise, and that a
knowledge management system could effectively support in-
structors in articulating and communicating that expertise. Based
on the requirements, we were able to derive the following design
principles, which have been rigorously observed.
(1) The framework should be implemented as a system. This
principle guarantees that the framework design will be
Table 1 KMSs for Managing Instructors’ Experience in Universities
Ref. KM ICT tool KM ICT category Main functionality
[10] JANET network Intranet Enables access to public knowledge comprising a
repository of electronic documents
[27] Web-based application developed
using WAMP (Apache server,
MySQL, and PHP)
Knowledge Portal Supports lecturers’ activities in institutions of higher
education through the sharing of useful lessons
learned
[28] Personal Blogs, Mental maps,
Virtual communities
Web 2.0, Knowledge maps Provides an environment for KM in higher education
and scientific research centers
[29] Wiki Web 2.0 Supports collaborative knowledge creation and sharing
in an academic environment
[30] NanoPort—Web portal Knowledge Portal Supports effective information searching and analysis
and enhances communication among researchers in
many scientific fields
[31] Knowledge portal using PHP Nuke Content management system Facilitates knowledge sharing and retrieval by enabling
publishing of faculty resources and storage in
repositories
[32] HELP CETL—Communication and
information sharing tool
Community of practice Develops communities of practice among university and
college staff
[33] Blog-based KMS Web 2.0 Enables faculty to share and transfer their knowledge
among themselves and with students
[34] INNOV—Knowledge portal using
WordPress
Content management system Creates an online community for university instructors
to share their experience and exchange innovative
teaching methods
[35] Info-Ca-Sh-Web portal, Blog and
Twitter
Knowledge portal, Web 2.0 Allows faculty members across higher education
institutions to capture and share tacit knowledge
[36] Knowledge Portal using JOOMLA,
PHP, and MySQL
Content management system Encourages knowledge-sharing culture among academic
staff
[37] InEdUn-Web portal using Drupal Content management system Encourages contact between innovation researchers to
promote creation of inter-university projects
EFFECTIVE REUSE AND SHARING OF BEST TEACHING PRACTICES 3

compatible with the prospective system architecture,
ensuring smooth conversion of the main processes into
modules.
(2) The design should be modular—that is, processes should
be identified, logically partitioned, and implemented as
modules. Modularity refers to the separation of concerns
and the division of the problem into processes that focus
on logical and well-defined aspects of the problem.
(3) Processes should exhibit independent functional character-
istics and should be separated from their resources.
This design principle enforces a simple interconnection
between processes and a consequent low coupling between
system modules, which need to be able to communicate,
exchange data, and access a range of diverse resources.
(4) Quality metrics should be defined to measure the
framework’s core processes. Metrics are tools for gauging
the quality of the core processes—in this case, the
acquisition and sharing of knowledge.
(5) The design should be communicated using a representa-
tion that is accessible to a large audience. The design
should hide the complexity of formulations, program
codes, and technical concepts, using commonplace icons
and terms.
In developing the system, we adopted a prototyping
approach, implementing an initial prototype that focused on the
process of knowledge acquisition. The prototype was used to feed
back the framework design, resulting in the addition of
“knowledge scoring” as a new process. Also the use of the
prototype was an opportunity to validate the human-machine
interaction and more specifically the elicitation phase where web
forms have been used to gather the user expertise. The design
generated five processes: acquisition, scoring, retrieval, sharing
and reuse.
KNOWLEDGE MANAGEMENT FRAMEWORK
Knowledge management of educational expertise is of great
importance in order to capitalize recent teaching innovations and
to channel the significant advances in e-learning and technology-
enhanced education [43]. Instructors should be able to record their
own teaching innovations and experiences and should be
encouraged to share these for the benefit of learners. The main
challenge is to persuade instructors to share their expertise and to
interact with their peers. To that end, we have developed a KM
framework, implemented as a system that shares best teaching
practices. The system supports and stimulates instructors,
educators, and communities to articulate their expertise in
teaching and to share it with their peers. The proposed framework
is based on two key principles. The first of these is free-user
contribution, which means that any proposed contribution by any
instructor is welcome, with no control or moderation that is done to
accept or reject a contribution. The second is peer scoring of
knowledge, which means that any contribution will be peer-scored
by other users and will attract a high score if frequently reused,
liked, and positively commented. The objective of these two
principles is to initiate voluntary contribution and to ensure fair
evaluation and feedback from specialists. The proposed frame-
work promotes interaction between users and provides a
collaborative environment that promotes cooperation in knowl-
edge construction and content sharing, resulting in a direct
advantage to the contributor. To ensure equality of interaction
and collaborative construction of knowledge, content will be
completely provided by registered users.
Many authors have outlined the reasons why people act on a
voluntary basis, usually highlighting private and social motiva-
tions. Private motivations refer to “the imperative or need we have
to feel autonomous, competent and skilled human being” while
social motivations refer to “the need to share as well as the need to
belong to a group” which is a way to define oneself at the
professional level [34]. Another motivation is the scientific
recognition by university pairs [34]. As depicted in Figure 2, the
proposed framework has been designed to decouple processes
from resources and to isolate and represent as layers the processes
that contribute to KM of instructors’ expertise.
Users
The first layer of the system is the user layer, which handles the
different types of user who interact with the system. Instructors
and education experts are potential users who may provide, use,
and share expertise. The framework accommodates special groups
of users working as communities and sharing expertise related to
specific topics of interest. A community of practice is a “group of
practitioners with a common purpose who agree to work together
to solve problems, share knowledge, cultivate best practice and
foster innovation” [44]. In establishing a community of practice,
potential members will need communication tools for joining the
community; as the community of practice matures and becomes
more self-supporting, members need other tools to facilitate
knowledge sharing. In the proposed framework, the community of
Figure 1 Framework design. [Color figure can be viewed at wileyonlinelibrary.com]

practice has been established as a strategy for promoting sharing
and reuse of best practices among groups of instructors teaching
specific disciplines. It is effectively a learning forum, where
instructors collaborate to teach and learn from each other.
Knowledge Acquisition
The second layer is the knowledge acquisition layer, which allows
users to input their expertise to the system. Capturing the expertise
of instructors and education experts is a process that must be
handled with care; the objective is to enable them to articulate their
teaching experience and BTPs in a fluent and consistent way. This
is achieved by means of a four-step process: Identification,
Elicitation, Representation, and Validation.
Identification. Identification means helping users to detect and
recognize BTPs that add value to the learning process and that can
be reused by other users. A set of guidelines allows users to judge
whether the intended BTP worth adding to the system. These
guidelines include the following: “a BTP can be a method that
clearly adds value in teaching a course by saving time orclarifying
a concept;” “a BTP should have been applied in your teaching
and is confirmed to provide better results.” It is worth noting that
the system provides guidance to users in the identification of
interesting best practices but does not prevent them from adding
their own contribution. Users are encouraged to contribute by
adding their BTPs and interacting with their peers.
Elicitation. This step allows users to input the BTP to the system.
For this purpose, the user needs to provide concise information and
the requisite teaching material that describes the BTP, its benefits
for teaching, and how it has been used in teaching a specific
subject. The elicitation model has been developed to assist users in
describing various BTPs by controlling the type of information
requested and providing a suitable template to capture the user’s
expertise.
Representation. This step aggregates the data and material
entered by the user during the elicitation step and encodes it
into the system under a new BTP with a unique identifier. We used
Figure 2 Knowledge management framework. [Color figure can be viewed at wileyonlinelibrary.com]

a frame-like representation language [45] to enable the system to
cope with the diversity and richness of users’ expertise and to
provide flexibility in handling new types of best practice.
Validation. Validation completes the knowledge acquisition
process. During this step, the system checks the consistency
and completeness of the BTP. The user may be asked to update
some data items (such as the title, to avoid duplication) or to add
teaching material to make the BTP usable by others. Finally, the
BTP is presented in its final form to the user for validation and
storage in the system.
Knowledge Scoring
The framework implements an extrinsic motivator based on a
reward system for scoring BTPs. The scoring function combines
three weighted component measures: (1) author score, measuring
the relevance of an author based on his contribution in the system;
we developed a mechanism for calculating points based on
multiple criteria such as number of contributions and average
rating on all contributions made; (2) feedback, representing the
degree of satisfaction of other users who have shared and reused
the BTP; and (3) comments, based on the feedback of users who
did not use the BTP. The scoring function is a reward system that
measures the importance of the contributor and the reputation of
the BTP. When community members interact with a specific BTP
as users or simply by adding comments, they automatically affect
its rating. Reputation points represent the contributor’s reputation
within the community, which is calculated on the basis of their
contribution and interaction with other community members.
Earning reputation points by contributing knowledge can
encourage an individual to become more involved when they
recognize this acknowledgement by others. The scheme for
adjusting the weighting of component measures needs to be tested
and evaluated in real life, but this is beyond the scope of the
present work; more research on this issue is planned in the future.
Knowledge Retrieval
BTPs can be searched or browsed in the system. Browsing relies
on the categorization of BTPs by the system, where each is
associated with one or more categories. Searching is conducted by
means of a query system, which handles user queries and also
relies on a BTP’s score and context of use. For knowledge
consumers, seeking BTPs that fit their needs, it is very important to
be able to search the system by means of queries. As the system
uses a scoring system, BTPs will be ranked according to their
scores, which represent their relevance and estimated quality. The
system also uses the context associated with each BTP, which is
matched to the user’s context. To provide a KMS that is practical,
effective, and easy to use, we implemented three methods of
knowledge retrieval: (1) keyword-based, in which the query is
processed and the extracted query keywords are matched against
the taxonomy used to categorize BTPs; the results are ranked
according to the number of matched concepts between the search
query terms and the taxonomy concepts; (2) context-based, in
which BTPs are retrieved by matching the BTP’s context of use
and the user’s profile, including professional data and interests and
preferences; and (3) Quality-based, which relies on the BTP score,
calculated on (i) implicit feedback (e.g., downloads, views, and
bookmarks); (ii) explicit feedback (e.g., ratings); (iii) resource
characteristics (e.g., description and multimedia); and (iv) user
reputation points. Other information retrieval and text mining
techniques such as document translation and summarization can
also be integrated in the search component to improve the
overview of retrieved documents and to enable the user to perform
further analysis.
Knowledge Sharing
Knowledge sharing is an essential component of the framework and
uses diffusion strategies to reach the right knowledge consumers at
the right time. Two strategies have been defined for diffusing
knowledge and creating interaction among users: the push strategy
and the feedback strategy. The push strategy consists in
disseminating newly added content to potential interested users.
Context matching is used to define and target potential interested
users. The feedback strategy initiates a form of interaction between
users by immediately notifying an author whenever their BTP is
reused or commented by another user. Other strategies have been
studied with a view to developing effective knowledge sharing by
using more sophisticated methods to identify the target user
population and using Web 2.0 technologies to disseminate both
notifications and content that allows users to learn and interact.
Knowledge Reuse
The main objective of knowledge reuse is to allow the knowledge
consumer to access and apply BTPs. As BTPs are context based,
they generally need to be adapted to the new context in which they
will be applied. For this purpose, the framework uses case-based
reasoning (CBR) [46]; this is very suitable, as a BTP applied in the
context of the author it can be adapted and reused in the new
teaching context of the knowledge consumer, leading to a new
BTP to be stored in the system. CBR is a four-step cycle: Retrieve,
Reuse, Revise, and Retain. To support reuse of BTPs, the
framework encourages authors to specify (at time of creation)
where and how the BTP can be reused in other contexts; this
information can then be searched by knowledge consumers.
SYSTEM IMPLEMENTATION
The framework has been implemented as a KM system that runs as
a server, offering services to users through the web. The system
includes two main modules: the knowledge portal and the
application manager.
Knowledge Portal
The knowledge portal has been developed using Drupal (drupal.
org), a free community-supported content management system for
creating, organizing, presenting, and managing a website [47].
The portal runs on a computing platform that supports Apache,
PHP, and MySQL to store content and settings. Moreover, Drupal
offers the programmer more flexibility than other existing content
management systems in developing user-specific applications.
The knowledge portal features a dynamic graphical user
interface that runs on the client side and handles all user requests
and collaborative activities. It facilitates knowledge acquisition,
sharing, and retrieval by enabling users to publish documents,
share ideas, work collaboratively, and store knowledge in a readily
searchable repository. Figure 3 illustrates the homepage of the
knowledge portal.

The knowledge portal also authenticates users and manages
rights and authorizations for each user within a more broadly
defined university community. The portal provides an intuitive
graphical user interface that facilitates input of BTPs by allowing
instructors to describe them in a fluent way. These are then stored
in a database so that other instructors can search and reuse them.
Moreover, the portal disseminates best practices to instructors on
the basis of their profile and interests. The system also promotes
sharing of BTPs by evaluating scores based on the most used
and most commented. The portal employs a range of techniques
to encourage the community to become more involved and
self-supporting. Discussion forums are set up to foster member
engagement and sharing of expertise and information. Members of
the same forum come from the same discipline, and there is a
dedicated forum for each discipline: computer science, math,
engineering, and so on. The portal also captures and shares “know-
how” expertise by means of “blogging,” where instructors with the
same interest are assigned to groups to contribute and post their
experiences. Unlike forums, these groups are based on interests
rather than disciplines. Examples of groups include “first-year
teaching,” “postgraduate studies,” and “textbook review.” A
typical list of groups is illustrated in Figure 4.
Content provided by users can take several forms: text,
graphics, presentations, multimedia, and hyperlinks to web
resources, applications, software, and so on. Every piece of added
content can be exploited when the BTP is reused by other users. A
typical BTP template (Fig. 5) includes the following information:
title, profile, context, resources, description, lessons learned, links
to resources, and tools and techniques.
Additionally, links to member information are set up to
connect members together (Fig. 6). This technique helps to
improve social community practices among members, and several
other techniques are used to enlist members and facilitate
their contact with others, including e-mail, chat, and instant
messaging [48].
Application Manager
The application manager runs the applications and programs
that have been developed to provide services to users on the
server side. The application manager implements the framework
processes: knowledge acquisition, scoring, retrieving, sharing,
and reuse. Knowledge acquisition, sharing, and reuse processes
are invoked by the user from the portal. They are executed
whenever the user asks to create, consult, or reuse a BTP; specific
web forms are displayed to the user, requesting or displaying
information. Knowledge scoring is implemented as a function
that continuously calculates BTP scores and author reputation.
Knowledge retrieval entails use of the search module to retrieve
query-related contents from the portal database using Solr, which
is the most popular enterprise search engine by virtue of features
such as full-text search, hit highlighting, faceted search, real-time
indexing, dynamic clustering, database integration, NoSQL
features, and rich document handling (e.g., Word, PDF).
When a search query is submitted to the portal, the query is
forwarded to the search engine, which compiles the results and
presents them to the user. As in most search engines, the results are
presented as a ranked list. Users may select the method of ranking
search results, by relevance, novelty, user rating, or recommended
content. The system can re-rank results based on a quality metric,
presenting them to the user as recommended content. Addition-
ally, faceted browsing helps to refine search results by returning
organized content, allowing the user to explore the list of search
results smoothly and easily. Facets correspond to knowledge
attributes, which are derived from representations of the BTP such
as keywords, level of course, subject, and material type.
CASE STUDY
To demonstrate SBPoT’s portal capabilities, a scenario involving
two different users will be used to demonstrate how BTPs are
Figure 3 Knowledge portal homepage. [Color figure can be viewed at wileyonlinelibrary.com]

managed in this KMS. Yasser is an instructor at the university. He
teaches bachelor students a course on “Introduction to Database
Systems,” which is mandatory for students in the Information
Systems Department. One of the main topics on this course is
“Database Design,” which examines the process of producing a
high quality relational database schema. Following many years of
experience in teaching database design, Yasser has developed a set
of teaching practices that he considers to be very efficient for
Figure 4 List of groups. [Color figure can be viewed at wileyonlinelibrary.com]
Figure 5 Example of a template. [Color figure can be viewed at wileyonlinelibrary.com]

explaining this topic, and he decides to share these experiences
with his colleagues. Initially, he wants to present a list of “hints for
good database design” that he has used to help students quickly
and easily design databases (Fig. 7).
The system is based on the concept of voluntary contribution
for knowledge sharing among instructors. To be able to input his
best practice, Yasser needs to log into the system by means of a
graphical user interface (GUI). The system offers a range of
templates to support instructors in this knowledge creation step.
He selects the appropriate template and enters an explanation of
his experience. In addition, he adds a slide presentation that
explains in detail the three hints, with examples, and a tutorial
document to be solved by students, along with solutions. The files
are added as resources and are uploaded when the BTP is
uploaded.
Sara is a novice instructor at another university who is about
to teach database courses for the first time. She decides to take
advantage of others’ experiences to teach her course. She can log
into the system and search about any specific topic; for example,
when Sara submits a keyword-based query like “Database
Design”, the query will be forwarded to the search engine and
the database, and the search results will be compiled and presented
as in Figure 8. Sara will see a wide-ranging set of search results,
presented as a list, ranked according to the ranking method
she selects: recommended, date submitted, or average rating. The
system also has a smart evaluation system and can re-rank the
results based on a quality score, presenting them as recommended
contents. When Sara clicks on the title of a search result, a screen
of detailed information allows her to view, download, share,
bookmark, or rate content (Fig. 9). Furthermore, a list of related
recommended contents enables her to more easily identify
documents of interest. For further clarification, Sara can
communicate with other users by chatting, sending e-mail,
initiating discussion in forums, or joining groups.
BTP QUALITY METRICS
Reusing best practices in teaching is an approach aiming to
capitalize and exploit experiences of teachers and to communicate
them to the community of teachers in order to be reused. The
objective in reusing BTPs is to leverage the quality of instruction
and to boost interaction and collaboration among the community
of instructors. But how to evaluate the proposed approach? How to
assess the efficiency of the implemented system and make sure
that sharing and reusing BTPs contribute to enhance the quality of
instruction? Learning is a cognitive process that involves human
and environment aspects. Human aspects includes a set of factors
such as knowledge, skills, and abilities. On the other hand,
environment aspects include factors embedded in the context of
learning such as learning material, teaching activities, assess-
ments, learning objectives and outcomes. While human factors
have a critical impact on the learning process, they can hardly be
assessed. Conversely, environment factors are tangible and can
be measured. The motivation in defining BTP metrics is to give
system users an appreciation of the reuse cost and the added value
that may occur in reusing a BTP in their e-courses. The reuse cost
represents the effort devoted by the instructor in reusing a BTP.
This includes the effort in searching the right BTP while using the
system, the effort that is needed to adapt the existing learning
material to accommodate the new BTP and the effort that is needed
to integrate the BTP within the e-course. The added value is an
appreciation of the effect that a BTP has on the different learning
units of the e-course and also sometimes on other e-courses that
Figure 6 Member information. [Color figure can be viewed at wileyonlinelibrary.com]

may be influenced by the use of the BTP. Indeed, some BTPs
represent pedagogical methods that are used by some instructors in
teaching a diversity of courses.
In order to evaluate the quality of BTPs we have defined
in this work a set of metrics relying on measurable and
observable environment aspects. Some of these metrics have
been adapted from the software engineering field. Indeed,
reusing BTPs in e-learning is comparable to Component Reuse
in software engineering which consists in reusing existing
software components (e.g., source code, object-oriented
classes, components, patterns) in the development of a new
software [40].
Figure 7 Example of a contribution. [Color figure can be viewed at wileyonlinelibrary.com]

BTP Reuse Effort
The first metric is the effort Ereuse of reusing a BTP in a Learning
Unit (LU). This metric estimates the human effort required to
reuse the BTP. It is important for instructors to have some sense of
the expected effort in reusing a BTP, which should not generate
an unnecessary overhead for their course authoring activities. We
used two different methods for calculating reuse effort: the first
method quantifies the human effort as person per unit time
(person-hour), and the second uses the size in kilobytes (KB) of
both the BTP and the LU.
Reuse effort Et
reuse in person-hours is expressed by the
following equation:
Et
reuse ¼ Eselection þ Especialization þ Eintegration; ð1Þ
where Eselection is the effort of searching for a BTP to be reused,
which includes querying the database and selecting and retrieving
Figure 8 Search result. [Color figure can be viewed at wileyonlinelibrary.com]
Figure 9 Detailed resource information. [Color figure can be viewed at wileyonlinelibrary.com]

the BTP. This item is measured by the system as the time spent by
the user in searching for a BTP. Especialization represents the effort
required to adapt the BTP to fit the learning unit. Eintegration is
the effort required to incorporate the BTP into the LU. (These
two latter variables are estimated by the user).
Reuse effort using the size Es
reuse is expressed by the
following equation:
Es
reuse ¼ SBTP þ r Â SLU; ð2Þ
where SBTP is the size of the BTP in kilobytes (KB); SLU is the size
of the learning unit (in KB); and r represents the fraction of the LU
that has been updated to integrate the BTP. For a slide presentation,
a document including notes, or any similar material used in both the
BTP and the LU, r is calculated as the ratio between the number of
BTP slides or pages over total slides (or pages) in the LU. Where
there are other complex media files such as videos, flash animation,
applications, figures, or images, the user is asked to estimate r by
answering the following question: “What portion of the learning
unit was modified to accommodate the BTP?”
To arrive at a standardized effort metric, the following
incorporates both reuse efforts and is defined as the average of
Et
reuse and Es
reuse:
Ereuse ¼ Et
reuse Â 10 þ Es
reuse
À Á
=2: ð3Þ
Ereuse uses two different calculation metrics, representing
instructor effort and size of learning material handled. To ensure
that Ereuse provides a good estimate of reuse effort, user validation
is needed whenever the measures of the variables are taken
automatically by the system.
BTP Impact
Reuse effort alone cannot deliver a sense of a BTP’s effectiveness,
as some BTPs require less effort and can be very effective in
teaching while others require significant effort and have less
impact on teaching. Another metric that helps in evaluating the
effectiveness of a BTP is the BTP Impact IBTP which represents the
BTP’s applicability to other learning units (of the same course or
of other courses). Some BTPs may be applicable beyond the
current unit and can be further reused. Some BTPs can be reused
within the LU under development; some can be reused in other
LUs of the same course; and in some cases, reuse of a BTP may
extend beyond a given LU and course to be reused explicitly or
implicitly in other courses. For instance, the BTP “reducing a 1-h
lecture’s objectives to a maximum of three objectives” can be
adopted in the LU under development, and if the instructor finds it
effective, they may adopt it in preparing other LUs of the same
course and may possibly reuse it for other courses. On that basis,
we defined the impact of a BTP IBTP as a metric that takes account
of LUs and courses that might potentially be affected (explicitly or
implicitly) by the BTP in the instructor’s subsequent authoring
activities:
IBTP ¼ 1 þ acourse Â hLU þ ateaching Â hcourses; ð4Þ
where acourse and ateaching are weighting factors, representing the
respective importance of nLU (the number of LUs in the current
e-course) and ncourses (the number of e-courses that will be affected
by the BTP). Note that IBTP is 1 if the BTP has an impact only on
the current LU. nLU and ncourses are estimated by the instructor.
BTP Effectiveness
The following metric was defined to reflect the added value of a
BTP on instructors’ authoring activities. wBTP represents the
effectiveness of reusing a BTP as the degree to which reusing the
BTP has been successful in enhancing the quality of instruction
from the instructor’s point of view. It is calculated as the ratio
between the impact of a BTP and the effort of reusing it:
wBTP ¼ IBTP=Ereuse ð5Þ
The effectiveness metric is important for BTPs that influence
multiple LUs and courses while necessitating less effort. Note that
Ereuse cannot be null because Eintegration (Equation 1) cannot be
null, as any BTP requires an effort to achieve integration in the LU.
SYSTEM EXPERIMENTATION
To evaluate and validate the use of the metrics defined in the
previous section, we conducted a system experiment with actual
data. A set of 12 BTPs most often used in the system were chosen
as a sample. These BTPs have been shared and reused by
instructors who are members of an active group teaching database
concepts. Although most of these BTPs relate to database
concepts, BTP1 and BTP9 relate to pedagogical aspects of
teaching, which means that they can be used in many courses. The
first experiment calculated reuse efforts using Equations (1–3).
Table 2 shows (from left to right) the BTP Id, a brief description of
the BTP, and the measures of calculated reuse efforts for each
BTP. Eselection is measured by the system as the effort (in person-
minutes) required to search for and retrieve a BTP in the system.
Especialization is estimated by the user and represents the effort
required to adapt the BTP to the learning unit. This variable is null
for BTP1 and BTP10, which means that the BTP itself needs no
adaptation for reuse in the LU. Eintegration is also estimated by the
user and represents the effort of incorporating the BTP in the LU.
For instance, for BTP1, the user needed 10 min to update his LU to
accommodate the BTP, reducing the lecture objectives from five to
three as recommended by the BTP. Et
reuse is the sum of the three
previous variables calculated by Equation (1). SBTP is the size of
the BTP in kilobytes (KB), and SLU is the size of the learning unit
(in KB). These two variable measures are obtained automatically
by accessing the file system. r represents the fraction of the LU
updated to integrate the BTP. For instance, BTP1 is a slide
presentation of 355 KB, the instructor’s LU is a slide presentation
of 975 KB, and 12% of the LU has been updated to accommodate
the BTP. Es
reuse reports the reuse effort using the size of files as
calculated by Equation (2). Ereuse (as calculated by Equation 3)
incorporates both reuse efforts Et
reuse and Es
reuse. Note that the
results in Table 2 are ordered by Ereuse values.
Figure 10 represents the efforts calculated for the 12 BTPs
used in the experiment. Clearly, there is no major difference
between the two calculated efforts Et
reuse and Es
reuse for almost all
the BTPs other than BTP3 and BTP9 because of the relatively
small LU sizes used in the experiment. Indeed, the size of LU may
vary, depending on the length of the instructor’s slide presentation
and the media file type, which may noticeably increase or decrease
Es
reuse. Nevertheless, the effect of such extreme measures of
Es
reuse is moderated in the calculation of Ereuse, which averages
reuse effort and assigns a higher weight to Et
reuse (see Equation 3).
The second experiment was designed to calculate the impact
and effectiveness of the 12 BTPs used in the first experiment.

Table 3 shows nLU (the number of LUs in the current e-course
affected by the BTP) and ncourses (the number of e-courses affected
by the BTP). nLU and ncourses are estimated by the instructor, who
evaluates how many additional LUs and e-courses will be affected
by the given BTP. For instance, BTP11 is used within the e-course
Database Concepts only and has no impact on other LUs (nLU ¼ 0)
but affects another e-course (Advanced Database Systems), as
concepts of normalization are reviewed in this second e-course,
enabling reuse of BTP11 (ncourses ¼ 1). IBTP is the BTP impact,
calculated using Equation (4), and wBTP is BTP effectiveness,
calculated using Equation (5). Note that the wBTP and IBTP have
been normalized to fit within the graph’s range values in Figure 11,
and that the results in Table 3 are ordered by values of wBTP.
The effectiveness metric gives a clear indication to users of
the most effective BTPs. In Figure 11, BTP1 and BTP2 are the
most effective, as they require low reuse effort and have a
high impact. On the other hand, some BTPs (BTP12, BTP11,
BTP10, and BTP9) require substantial reuse effort while apparent
effectiveness remains low. Effectiveness, effort, and impact
metrics are calculated and displayed beside each BTP to give users
a sense of the complexity of reusing a given BTP in their own
learning units and e-courses. To evaluate the appropriateness of
the metrics defined in this work, users who have used a BTP are
invited to provide feedback on the accuracy of the metrics and
whether they correctly reflect the effectiveness of the BTPs in use.
For this reason, it is planned to implement a quality module that
will evaluate user satisfaction to allow direct comparison of
effectiveness as measured by metrics against real users’ feedback.
DISCUSSION
The development of the SBPoT framework for KM and the use of
the system by a community of instructors yielded a number of
interesting findings. First, the KM approach seems best suited to
handling instructors’ expertise, as this takes the form of an
accumulation of experiences and best practices to be articulated
through an elicitation phase, helping instructors to identify and
gradually specify their expertise using well-specified web forms.
Second, the framework has been designed through iterative cycles
Figure 10 Reuse effort for BTPs. [Color figure can be viewed at wileyonlinelibrary.com]
Table 2 Reuse Effort for Most-Used BTPs
BTP
Id Best teaching practice Eselection Especialization Eintegration Et
reuse SBTP SLU r Es
reuse Ereuse
BTP1 Reducing 1 h lecture’s objectives to a maximum of three 24 0 10 34 355 975 0.12 472 406
BTP2 Three hints for a good database design 18 10 10 38 467 1980 0.07 606 493
BTP3 Six steps for mapping an ER diagram into a relational
model
47 25 25 97 255 390 0.13 306 638
BTP4 An easy method to check the BCNF for a relational schema 45 15 25 85 546 810 0.15 668 759
BTP5 How to select the primary key among a list of candidate
keys
36 26 43 105 360 1430 0.1 503 777
BTP6 Teach normal forms in databases using simple examples 44 22 40 106 280 810 0.4 604 832
BTP7 Five common mistakes to avoid when designing a database 45 28 65 138 425 1430 0.12 597 989
BTP8 Using knowledge maps for teaching database concepts 32 60 40 132 226 2120 0.35 968 1144
BTP9 Using a team-based approach in teaching 47 23 110 180 620 2120 0.07 768 1284
BTP10 An easy tutorial for teaching SQL 26 0 106 132 325 1757 0.55 1291 1306
BTP11 Teach normalization in three simple steps 32 39 106 177 478 810 0.62 980 1375
BTP12 Teaching the ER data model before the Relational data
model
41 50 120 211 525 4044 0.15 1132 1621

and progressively refined to arrive at five processes: elicitation,
scoring, retrieval, sharing, and reuse (see Fig. 2). This approach
has helped to clearly identify the system functions, which were
mapped naturally into the system as services and applications
during the implementation phase. Third, instructors who
contributed to the system expressed satisfaction that their
contributions were scored by the community of instructors, as
this is effectively scientific peer recognition, which boosts social
interaction as well as motivating and promoting them at
professional level. Fourth, while observing users at work, we
noted that they interacted very well with the graphical user
interface (GUI), with no major difficulty and without any prior
formal training. Indeed, the GUI was designed to comply with
software usability criteria and to be comparable to social networks
commonly used by users. Fifth, the framework as developed is
intended to support instructors in delivering quality teaching and
to boost collaboration within specialized communities. Instructors
are encouraged to evaluate and share their experiences in reusing
a BTP, and such contributions are rewarded by the system,
impacting positively on the instructor’s reputation. System self-
evaluation is an interesting feature that we plan to implement as a
system module in the near future. Finally, when searching for and
retrieving BTPs in the system, most users made frequently use
of the scoring option to rank results, as they preferred to deal
with high-scoring BTPs (i.e., those that are most reused and
commented). Although this may seem a positive, the drawback is
that new BTPs may never be consulted and will not emerge as
interesting options. This led us to work on adapting the scoring
function to give newly created BTPs a chance to be retrieved
and consulted by users even though their score is low. A number
of options are being studied and evaluated with a view to
implementing a fair policy in this regard.
With regard to the metrics defined here, their purpose is to
give system users an accurate sense of BTP quality in terms of
reuse cost, impact, and effectiveness. These metrics rely on
measurable environmental factors that contribute directly to
sharing and reusing system BTPs. The experiments clearly show
that some BTPs are more effective than others, in that they have a
high impact on the instructor’s teaching and require less reuse
effort. The experimental results were presented to three faculty
staff at our college who had not used the system. Two of them (I1
and I2) have already taught the Database Concepts course while
the third (I3) teaches other subjects. After a session to introduce
and demonstrate the system, we discussed three main points with
each of them individually: the approach in general, BTP quality
and relevance of metrics, and possible extensions and uses of the
system. All three expressed their satisfaction with the approach as
a means of capitalizing, sharing, and reusing the experiences of
teaching colleagues, and all confirmed that this approach could
be a useful channel for the intended purpose. In respect of BTP
Table 3 Effectiveness of Most-Used BTPs
BTP Id Best teaching practice nLU ncourses IBTP Ereuse PHIBTP
BTP10 An easy tutorial for teaching SQL 0 0 100 1306 77
BTP11 Teach normalization in three simple steps 0 1 120 1375 88
BTP6 Teach normal forms in databases using simple examples 0 0 100 832 121
BTP7 Five common mistakes to avoid when designing a database 0 1 120 989 122
BTP3 Six steps for mapping an ER diagram into a relational model 0 0 100 638 157
BTP4 An easy method to check the BCNF for a relational schema 0 1 120 759 159
BTP5 How to select the primary key among a list of candidate keys 0 1 120 777 155
BTP12 Teaching the ER data model before the Relational data model 7 1 330 1621 204
BTP2 Three hints for a good database design 0 2 140 493 284
BTP8 Using knowledge maps for teaching database concepts 9 1 390 1144 341
BTP9 Using a team-based approach in teaching 10 6 520 1284 405
BTP1 Reducing 1 h lecture’s objectives to a maximum of three 12 6 580 406 1429
Figure 11 Effectiveness measure for BTPs. [Color figure can be viewed at wileyonlinelibrary.com]

quality and relevance of the metrics, I1 made no major comment
on the metrics; I2 pointed out that the quality of BTPs should take
account of feedback from both re-users (instructors) and students,
as they are part of the learning process. This suggestion is
interesting, as the quality of BTPs will ultimately be evaluated and
scored by learners, but the present scope of the system is confined
to supporting instructors sharing their expertise. Additionally, I3
remarked that the effectiveness metric should take account of the
reuse effort for all LUs and e-courses involved in the calculation of
impact. This presupposes that all LUs and e-courses are already
prepared for estimation of reuse effort, which is not the case for all
instructors. Moreover, the impact on reuse effort of LUs in the
current e-course, and in other e-courses that will be affected by the
BTP, is regulated by the weighting factors acourse and ateaching
(see Equation 4), which have been set to low values (less than
0.3) to moderate their effect. With regard to extensions and uses
of the system, I1 and I2 suggested that it could be very effective
if coupled with the learning management system currently in
use at the college, and I3 noted that a mobile version of the
system would be a very attractive option for instructors, enabling
them to use it anytime and anywhere. These two suggestions
are under consideration and are likely to be among our next
system extensions.
CONCLUSION
The knowledge management framework presented in this paper
aims to capitalize and share teaching experiences in education.
The framework allows instructors to articulate their know-how in
teaching as BTPs, representing long-established experiences
developed through teaching. The framework has been imple-
mented as a system that allows instructors to identify and elicit
BTPs in a fluent way and provides functionalities to support
convenient search, sharing, and reuse by knowledge consumers.
Metrics defined in this work give system users an appreciation of
the reuse cost and the added value of reusing a BTPs. The system
has been used and tested in real life within a community of
instructors.
We are currently developing a more sophisticated scoring
function to improve the visibility of newly added BTPs to the
system. Future work will focus on deploying the system on
the web to test and evaluate its full capabilities. This will
necessitate resolving a couple of issues such as the implementation
of a secure authentication mechanism for users and communities,
copyright issues related to user contributions, and diversifying
and optimizing search techniques to incorporate the contributions
of knowledge consumers. We are also planning to implement a
module that will evaluate user satisfaction from instructors’
feedback in reusing BTPs and thus will allow a direct comparison
of the effectiveness as measured by metrics and resulting from
real users’ feedback.
ACKNOWLEDGEMENT
This work was supported by the Research Center of College of
Computer and Information Sciences, King Saud University. The
authors are grateful for this support. [Correction added on 20
February 2017, after first online publication: Acknowledgment
section has been added.].
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BIOGRAPHIES
Amal Al-Rasheed is a PhD candidate in the field of knowledge
engineering. In 2003, she received her MSc in computer science at the
College of Computer and Information Sciences, King Saud University,
Saudi Arabia. Since 2003, she is working as a lecturer at Princess Nourah
Bint Abdulrahman University – Saudi Arabia. Her research areas of
interest include knowledge engineering, e-learning, web development,
and data mining.
Jawad Berri is a faculty member at King Saud
University – Saudi Arabia. He received his PhD in
ComputerSciencefromParis-SorbonneUniversity
in France in 1996. Jawad’s research interests focus
on context-aware systems, learning technologies,
mobile systems, and natural language processing.
He has been involved in many projects related to
mobile learning, semantic web, automatic summa-
rization, web information filtering, and mobile
agents for web information discovery. He worked
as a researcher at the CNRS – the French National Research Center, the
Computer Science Institute at the University of Zurich – Switzerland and
Sonatrach – the Algerian Petroleum and Gas Corporation. Jawad has held
positionsattheUnitedArabEmiratesUniversity,KhalifaUniversityofScience
Technology and Research and King Saud University. His contributions in
researchprojectsintheindustryandacademialedtothepublicationofpapersin
numerous journals and conferences. Jawad is a senior member of the IEEE.

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