PYC3703 Complete Exampack
This document is a compilation of UNISA Assignment and Exam Questions and Answers
Answers are motivated by a combination of:
• Short summaries/reasoning regarding the relevant topic(s) in question. (Incorrect options are also marked where applicable, in order to identify and disregard red-herring alternatives)
Assignments covered are:
• 2016 Assignment 1 – Semester 1
• 2016 Assignment 2 – Semester 1
• 2016 Assignment 1 – Semester 2
• 2016 Assignment 2 – Semester 2
• 2018 Assignment 1 – Semester 1 - 788821
• 2018 Assignment 2 – Semester 1 - 773771
• 2018 Assignment 1 – Semester 2 - 759527
• 2018 Assignment 2 – Semester 2 - 726566
Exams covered are:
• 2013 Exam May-June
• 2013 Exam October-November
• 2014 Exam May-June
• 2014 Exam October-November
• 2015 Exam May-June
• 2015 Exam October-November
• 2016 Exam May-June
• 2016 Exam October-November
• 2017 Exam May-June
• 2017 Exam October-November
While the length of this document seems overwhelming, most of the questions and answers are repeated in more than one exam-paper and/or assignment. Therefore, there is a big amount of duplication in this document. However, this is not necessarily a bad thing, as the Prescribed textbook states on pg. 189, that the notion of ‘relearning’ pertains to “the general finding that a shorter period is needed, or that a ‘saving’ occurs, when you learn some information or task a second time. This effect probably stems from the fact that some residual memory relating to your first learning experience still remains, and this may facilitate the subsequent learning of the same information so that it now becomes easier.”
This document is compiled in chapter-sequence, instead of chronological order of the respective assignments and exams. This facilitates easier exam-reparation, as you can test yourself chapter-by-chapter as you go along, and not only once all the material has been studied. Please note that some questions refer to more than one chapter, i.e. some of the answers from Chapter 4 could also be found in Chapter 13. Therefore, it remains necessary to study the questions in this document under Chapter 4. Also note that this means that some questions may appear to be under the incorrect Chapter listed in the sequence below. Note that question numbers therefore do not relate to the papers it was asked in; it follows numerical order of this document.
Please note: This document is an additional tool for exam preparation. The Stuvia-user that compiled and uploaded this document takes no responsibility for incorrect answers. Students must ensure that they study the prescribed material and understand the content.
Collegeslides and notes from Theory of Learning and Instruction
Clear and extensive notes from the lectures of Theory of Learning and Instruction. The information from the slides has been processed in these notes. The information from the slides is bold and the notes are written in regular text. All images from the slides are also included. The lecture notes are written in English.
Learning in organizations
Week 1 Evaluating organizational change
Boonstra, J.J. (2004) Dynamics of organization change and learning: Some reflections and perspectives on organizing, changing, and learning.
Nielsen, K., & Randall, R. (2013). Opening the black box: Presenting a model for evaluating organizational-level interventions.
Guba, E. G., & Lincoln, Y. S. (1994). Competing paradigms in qualitative research.
Week 2 Formal & informal learning in organizations
Salas, E., Tannenbaum, S. I., Kraiger, K., & Smith-Jentsch, K. A. (2012). The science of training and development in organizations: What matters in practice.
Blume, B. D., Ford, J. K., Baldwin, T. T., & Huang, J. L. (2010). Transfer of training: A meta-analytic review.
Eraut, M. (2004). Informal learning in the workplace.
Edmondson, A. C. (2002). The local and variegated nature of learning in organizations: A group-level perspective.
Week 3 Organizational learning
Engeström, Y., Kerosuo, H., & Kajamaa, A. (2007). Beyond discontinuity: Expansive organizational learning remembered.
Handley, K., Sturdy, A., Fincham, R. and Clark, T. (2006). Within and beyond communities of practice.
Handley, K., Clark, T., Fincham, R. and Sturdy, A. (2007). Researching situated learning.
Wenger, E. and Snyder, M. (2000). Communities of practice: The organizational frontier.
Week 4 Professionals, learning and development
Desimone (2009) Improving Impact Studies of Teachers’ Professional Development: Toward Better
Conceptualizations and Measures
Imants, Wubbels & Vermunt (2013). Teachers enactments of workplace conditions and their beliefs and attitudes towards reform
Stringfield, S., Reynolds, D., & Schaffer, E. C. (2008). Improving secondary students' academic achievement through a focus on reform reliability: 4- and 9-year findings from the High Reliability Schools project
Week 5 Beliefs about learning and a diverse population
Van der Krogt, F. J., & Vermulst, A. A. (2000). Beliefs about organizing learning: A conceptual and empirical analysis of managers’ and workers’ learning action theories.
Kyndt, E., Govaerts, N., Dochy, F., & Baert, H. (2011). The learning intention of low-qualified employees: A key for participation in lifelong learning and continuous training
Nauta, A., Vianen, A., Heijden, B., Dam, K., & Willemsen, M. (2009). Understanding the factors that promote employability orientation: the impact of employability culture, career satisfaction, and role breadth self-efficacy
Week 6 Caveat emptor: the dark side of learning
Alvesson, M. & Spicer, A. (2012). A stupidity-based theory of organizations
Crowther, J. (2004). ‘In and against’ lifelong learning: flexibility and the corrosion of character
Samenvatting blok 1.8 Learning Man
Complete samenvatting van blok 1.8 Learning Man (EUR). Inclusief alle artikelen. Heb er zelf een 8 mee gescoord!
Samenvatting Human Learning (7th edition)
Samenvatting van het boek Human Learning (7th edition) voor het vak Leren & Cognitie.
Deze samenvatting bevat alle stof uit het boek aangevuld met college-aantekeningen en extra afbeeldingen. Dus H1 t/m H15, uitgezonderd H2.
Full summary Machine Learning
Complete and comprehensive summary of the basic principles of machine learning, including k-nn, decision trees, perceptron, gradient descent, logistic regression and neural networks. Includes illustrations for clarification. from 2016-2017.
Samenvatting \'Human Learning\' van Ormrod
Samenvatting van het boek \'Human learning\' van Ormrod. Gemaakt aan de hand van het boek en colleges van het vak \'leren en cognitie\'. Ook handig voor het nvo-examen.
Learning Problems and Learning Disabilities - Extensive and well-organized lecture notes and information from the slides
Comprehensive and well-organized notes from the Colleges of Learning Problems and Learning Disabilities. The information from the powerpoints is also in this file. The bold text and images come from the slides. The notes are the regular text. The notes are in English.
Data Science: Machine Learning 2017/2018 - Summary Lectures
Full summary including an introduction of Machine Learning and algorithms, such as Decision Tree, Perceptron, Gradient Descent, Logistic Regression (classifier) and Neural Networks. This summary also includes a section about Feature Engineering. Extra context and illustrations/graphs are also given, which makes this field of study a bit more understandable.
Data Science: Machine Learning 2017/2018 - Cheatsheet
For the Machine Learning exam it is allowed to keep a cheat sheet of 1A4. This is specially made so that all subjects of this course are described in detail, such as Decision Trees, Perceptron, Gradient Descent, Feature Engineering, Logistic Regression and Neural Networks. You are allowed to bring cheat sheet (1A4) with you. On this cheat sheet, all the necessary information (and more) are available on just two sides of paper. The following subjects are included: Decision Trees, Perceptron, Gradient Descent, Feature Engineering, Logistic Regression and Neural Networks.