Abstract: E-learning platforms, such as Blackboard have two major shortcomings: limited data capture as a result of the limitations of SCORM (Shareable Content Object Reference Model), and lack of incorporation of Artificial Intelligence (AI) and machine learning algorithms which could lead to better course adaptations. With the recent development of Experience Application Programming Interface (xAPI), a large amount of additional types of data can be captured and that opens a window of possibilities from which online education can benefit. In a corporate setting, where companies invest billions on the learning and development of their employees, some learner behaviours can be troublesome for they can hinder the knowledge development of a learner. Behaviours that hinder the knowledge development also raise ambiguity about learner’s knowledge mastery, specifically those related to gaming the system. Furthermore, a company receives little benefit from their investment if employees are passing courses without possessing the required knowledge and potential compliance risks may arise. Using xAPI and rules derived from a state-of-the-art review, we identified three learner behaviours, primarily related to guessing, in a corporate compliance course. The identified behaviours are: trying each option for a question, specifically for multiple-choice questions; selecting a single option for all the questions on the test; and continuously repeating tests upon failing as opposed to going over the learning material. These behaviours were detected on learners who repeated the test at least 4 times before passing the course. These findings suggest that gauging the mastery of a learner from multiple-choice questions test scores alone is a naive approach. Thus, next steps will consider the incorporation of additional data points, knowledge estimation models to model knowledge mastery of a learner more accurately, and analysis of the data for correlations between knowledge development and identified learner behaviours. Additional work could explore how learner behaviours could be utilised to make changes to a course. For example, course content may require modifications (certain sections of learning material may be shown to not be helpful to many learners to master the learning outcomes aimed at) or course design (such as the type and duration of feedback).
Abstract: In this paper we propose a computer-aided solution
with Genetic Algorithms in order to reduce the drafting of reports:
FMEA analysis and Control Plan required in the manufacture of the
product launch and improved knowledge development teams for
future projects. The solution allows to the design team to introduce
data entry required to FMEA. The actual analysis is performed using
Genetic Algorithms to find optimum between RPN risk factor and
cost of production. A feature of Genetic Algorithms is that they are
used as a means of finding solutions for multi criteria optimization
problems. In our case, along with three specific FMEA risk factors is
considered and reduce production cost. Analysis tool will generate
final reports for all FMEA processes. The data obtained in FMEA
reports are automatically integrated with other entered parameters in
Control Plan. Implementation of the solution is in the form of an
application running in an intranet on two servers: one containing
analysis and plan generation engine and the other containing the
database where the initial parameters and results are stored. The
results can then be used as starting solutions in the synthesis of other
projects. The solution was applied to welding processes, laser cutting
and bending to manufacture chassis for buses. Advantages of the
solution are efficient elaboration of documents in the current project
by automatically generating reports FMEA and Control Plan using
multiple criteria optimization of production and build a solid
knowledge base for future projects. The solution which we propose is
a cheap alternative to other solutions on the market using Open
Source tools in implementation.
Abstract: We present a framework of researcher knowledge
development in conducting a study in mathematics education. The
key components of the framework are: knowledge germane to
conducting a particular study, processes of knowledge accumulation,
and catalyzing filters that influence a researcher decision making.
The components of the framework originated from a confluence
between constructs and theories in Mathematics Education, Higher
Education and Sociology. Drawing on a self-reflective interview with
a leading researcher in mathematics education, Professor Michèle
Artigue, we illustrate how the framework can be utilized in data
analysis. Criteria for framework evaluation are discussed.
Abstract: Knowledge development in companies relies on
knowledge-intensive business processes, which are characterized by
a high complexity in their execution, weak structuring,
communication-oriented tasks and high decision autonomy, and often the need for creativity and innovation. A foundation of knowledge development is provided, which is based on a new conception of
knowledge and knowledge dynamics. This conception consists of a three-dimensional model of knowledge with types, kinds and qualities. Built on this knowledge conception, knowledge dynamics is
modeled with the help of general knowledge conversions between
knowledge assets. Here knowledge dynamics is understood to cover
all of acquisition, conversion, transfer, development and usage of
knowledge. Through this conception we gain a sound basis for
knowledge management and development in an enterprise. Especially
the type dimension of knowledge, which categorizes it according to
its internality and externality with respect to the human being, is crucial for enterprise knowledge management and development,
because knowledge should be made available by converting it to
more external types.
Built on this conception, a modeling approach for knowledgeintensive
business processes is introduced, be it human-driven,e-driven or task-driven processes. As an example for this approach, a model of the creative activity for the renewal planning of
a product is given.
Abstract: This article discusses the concept of student ownership of knowledge and seeks to determine how to move students from knowledge acquisition to knowledge application and ultimately to knowledge generation in a virtual setting. Instructional strategies for fostering student engagement in a virtual environment are critical to the learner-s strategic ownership of the knowledge. A number of relevant theories that focus on learning, affect, needs and adult concerns are presented to provide a basis for exploring the transfer of knowledge from teacher to learner. A model under development is presented that combines the dimensions of knowledge approach, the teacher-student relationship with regards to knowledge authority and teaching approach to demonstrate the recursive and scaffolded design for creation of virtual learning environments.