MALKA211 Introduksjon til atferdsanalyse Emneplan

Emnebeskrivelsen finnes kun på engelsk. Velg engelsk versjon av nettsiden for å se fullstendig emnebeskrivelse.

Coursework requirements from MALK4000-401 and MALK4000-403 must be approved to participate and submit coursework requirements in MALKA211.  

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 characteristics of behavior analysis as a science
• explain core concepts and relations on classical conditioning, and operant conditioning
• discuss how prediction and control can be demonstrated in single-case designs
• describe and exemplify different measures of reliability
• discuss different methods of observation and recording of behavior
• describe core elements of behavior chains and different ways in which such chains can be established

Skills

The student can

• select the appropriate behavioral dimensions and methods for reliable measurement, and observe and measure behavior
• identify examples of respondent conditioning
• explain how a behavior chain can be established
• identify examples of the operant paradigm
• interpret data from line and bar graphs

Competence

The student can

• provide practical examples of respondent behavior
• provide practical examples of operant conditioning
• use and explain core concepts in behavior analysis to professionals in different branches communicate important aspects of behavior analysis as a science

Emnebeskrivelsen finnes kun på engelsk. Velg engelsk versjon av nettsiden for å se fullstendig emnebeskrivelse.

Coursework requirements from MALK4000-401, MALK4000-403, and MALKA211, or equivalent must be approved to participate and submit coursework requirements in MALKA214.

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 ethical considerations in functional and statistical analyses

Competence

The student can

• analyze data in a behavior change project

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

None

Individual home examination (multiple choice-test), 3 hours. Exam questions are in English.