|Website:||website containing additional information|
|Period:||period 3 (week 6 through 16, i.e., 2-2-2009 through 17-4-2009; retake week 22)
|Participants:||up till now 52 subscriptions|
|Schedule:||Official schedule representation can be found in Osiris|
|Teachers:||Dit is een oud rooster!
|week: 10||Mon 5-3-2018||13.30-16.30 uur||room: EDUC-ALFA|
|week: 15||Mon 9-4-2018||13.30-16.30 uur||room: EDUC-GAMMA|
|week: 27||Mon 2-7-2018||13.30-16.30 uur||room: EDUC-ALFA||retake exam|
|Note:||No up-to-date course description available.|
Text below is from year 2007/2008
|Contents:||The learning objectives of this course are:
The overall theme of the course is Software Product Management, the discipline and business process which governs a product from its inception to the market/customer delivery in order to generate biggest possible value to the business. Software product management is complex: there are many stakeholders, many responsibilities and fastly changing requirements. We will deal with the internal structures of methods and techniques for four particular areas within this domain, namely: requirements management, release planning, product roadmapping and portfolio planning.
- Providing of insight and skills into the systematic description, explanation and evaluation of all aspects of the methodology of ICT systems;
- Contribution to the collection of knowledge on method engineering;
- Be able to work and adapt methods, techniques and tools in various applications of Method Engineering.
Target group: Master students in Business Informatics, Content and Knowledge Engineering, Computer Science, and Cognitive Artificial Intelligence.
Student enrolling a master in february are advised to follow the course in their second year. This course is especially meant for those who are interested in a career as researcher, consultant, developer, or (project) manager.
Literature consists of a number of selected scientific papers.
|Course form:||The course consists of a 2-hour lecture and a 2-hour workshop every week. The rest of the work is self study. Each student will select a method or technique in the domain of Software Product Management, for which a paper will be written. Main tasks will be literature review and description of methods using the meta-modeling technique of process-deliverable diagrams. The contents of this paper have to be presented during the workshops and will be peer reviewed. |
|Exam form:||The course is run as a project, where several deliverables have to be produced. The deliverable grade is a weighted average for the following assignments:
The deadlines of the assignments are strict. For every working day you are late, we deduct one point of your grade. The peer review and the draft paper are not graded. However, failing to perform any of the assignments will result in no mark for the course.
The average (weighted) deliverable grade contributes to 60% of your final mark. An individual written examination in week 16 contributes to the other 40% to your final mark of the course. Lecture and workshop materials including notes are subject of this exam.
In order to pass the course your final mark should be 5.5 or higher. Furthermore, we use the following constraints:
- the deliverable grade should be 5.0 or higher;
- the exam grade should be 5.0 or higher.
In case one of these conditions is not met, your final mark is the lowest of the two grades.
- Topic description (25%)
Draft paper (0%)
Peer review (0%)
Final paper (30%)
Knowledge infrastructure entry (10%)
|Minimum effort to qualify for 2nd chance exam:||To qualify for the retake exam, the grade of the original must be at least 4.|
|Description:||Method Engineering is defined as the engineering discipline to design, construct, and adapt methods, techniques and tools for the development of information systems. Similarly as software engineering is concerned with all aspects of software production, so is method engineering dealing with all engineering activities related to methods, techniques and tools. |
Typical topics in the area of method engineering are:
- Method description and meta-modeling
- Method fragments, selection and assembly
- Situational methods
- Method frameworks, method comparison
- Knowledge infrastructures, meta-case, and tool support