Programplaner og emneplaner - Student
MALKA214 Experimental Design and Functional Analysis Course description
- Course name in Norwegian
- Eksperimentelle design og funksjonell analyse
- Study programme
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Master's Program in Behavioral ScienceMaster’s Program in Behavioral Science - Specialisation in Innovation and ImplementationMaster’s Program in Behavioral Science - Specialisation in Concepts and Applications
- Weight
- 10.0 ECTS
- Year of study
- 2022/2023
- Curriculum
-
FALL 2022
- Schedule
- Programme description
- Course history
-
Introduction
N/A
Required preliminary courses
Coursework requirements from MALK4000-401, MALK4000-403, and MALKA211, or equivalent must be approved to participate and submit coursework requirements in MALKA214.
Learning outcomes
On successful completion of the course, the student has the following learning outcomes classified as knowledge, skills and competence:
Knowledge
The student can
- describe and discuss reliability
- describe and discuss the term generality
- describe and discuss validity, threats to inference, and different types of validity
- explain the role of replications in experiments
- discuss variability related to single subject designs and group-designs
- describe and discuss advantages and disadvantages of various experimental designs
- explain repeated measurements and when to conduct such measurements
- describe fundamental elements of inferential statistics, including hypothesis testing
- describe and discuss experimental methods for conducting reinforcer assessment and the functional analysis of behavior
- describe the basic principles for hypothesis testing using the binominal and normal distributions
Skills
The student can
- design simple experiments
- run and interpret common statistical tests
- interpret graphical displays of behavioral data and to present data in graphical form
- discuss ethics concerning the functional analysis of behavior
Competence
The student can
- analyze data in a behavior change project
Teaching and learning methods
In the BSCA specialisation, campus-based lectures, discussions and exercises are the main teaching methods. Students read selected texts in advance for each day of class, and everyone is expected to participate in class through questions and through joining in discussion. In the BSII specialisation, the main teaching method is digital course sequences, and feedback on details of course content, and supervised discussion groups will be available during pre-determined time periods. Feedback on written assignments is used in both specialisations. Students must have download and installed SPSS on their computers before the course starts
Course requirements
The following required coursework must be approved before the student can take the exam:
- 2 individual assignments submitted digitally, each with a maximum length of 12.000 characters, including spaces. References are to be included in the 12.000 characters.
Assessment
Individual home;examination, 5 hours. Exam questions are in English. Students may submit their exams in Norwegian, Swedish, Danish or English.;
Permitted exam materials and equipment
All
Grading scale
Grade scale A-F
Examiners
One internal and one external examiner will assess all exams.