Topic B: Cognitive psychology

2.1.1 The multi-store model of memory (Atkinson and Shiffrin, 1968), including information processing, encoding, storage, retrieval, capacity and duration.

Use - multi-store model of memory to connect the rule to the data and decision in the question.

This matters because - multi-store model of memory determines what can be inferred or chosen; begin with the stated conditions and keep the conclusion tied to the evidence.

Example: apply - multi-store model of memory to one small, clearly defined case, show the key step or comparison, and explain the result in words.

Boundary: - Multi-store model of memory is not a universal recommendation. Check the syllabus scope, assumptions, units and the limits of the evidence before generalising.

2.1.2 The working memory model (Baddeley and Hitch, 1974) including the phonological loop, central executive, visual- spatial sketchpad, episodic buffer.

Use - working memory model to connect the rule to the data and decision in the question.

This matters because - working memory model determines what can be inferred or chosen; begin with the stated conditions and keep the conclusion tied to the evidence.

Example: apply - working memory model to one small, clearly defined case, show the key step or comparison, and explain the result in words.

Boundary: - Working memory model is not a universal recommendation. Check the syllabus scope, assumptions, units and the limits of the evidence before generalising.

2.1.3 Reconstructive memory (Bartlett, 1932), including schema theory.

Use - reconstructive memory to connect the rule to the data and decision in the question.

This matters because - reconstructive memory determines what can be inferred or chosen; begin with the stated conditions and keep the conclusion tied to the evidence.

Example: apply - reconstructive memory to one small, clearly defined case, show the key step or comparison, and explain the result in words.

Boundary: - Reconstructive memory is not a universal recommendation. Check the syllabus scope, assumptions, units and the limits of the evidence before generalising.

2.2.1 Designing and conducting experiments, including field and laboratory experiments.

Use - experiment design and conduct to connect the rule to the data and decision in the question.

This matters because - experiment design and conduct determines what can be inferred or chosen; begin with the stated conditions and keep the conclusion tied to the evidence.

Example: apply - experiment design and conduct to one small, clearly defined case, show the key step or comparison, and explain the result in words.

Boundary: - Experiment design and conduct is not a universal recommendation. Check the syllabus scope, assumptions, units and the limits of the evidence before generalising.

2.2.2 Independent and dependent variables.

Use - independent and dependent variables to connect the rule to the data and decision in the question.

This matters because - independent and dependent variables determines what can be inferred or chosen; begin with the stated conditions and keep the conclusion tied to the evidence.

Example: apply - independent and dependent variables to one small, clearly defined case, show the key step or comparison, and explain the result in words.

Boundary: - Independent and dependent variables is not a universal recommendation. Check the syllabus scope, assumptions, units and the limits of the evidence before generalising.

2.2.3 Experimental and null hypotheses.

Use - experimental and null hypotheses to connect the rule to the data and decision in the question.

This matters because - experimental and null hypotheses determines what can be inferred or chosen; begin with the stated conditions and keep the conclusion tied to the evidence.

Example: apply - experimental and null hypotheses to one small, clearly defined case, show the key step or comparison, and explain the result in words.

Boundary: - Experimental and null hypotheses is not a universal recommendation. Check the syllabus scope, assumptions, units and the limits of the evidence before generalising.

2.2.4 Directional (one-tailed) and non-directional (two-tailed) tests and hypotheses.

Use - directional (one-tailed) and non-directional (two-tailed) tests to connect the rule to the data and decision in the question.

This matters because - directional (one-tailed) and non-directional (two-tailed) tests determines what can be inferred or chosen; begin with the stated conditions and keep the conclusion tied to the evidence.

Example: apply - directional (one-tailed) and non-directional (two-tailed) tests to one small, clearly defined case, show the key step or comparison, and explain the result in words.

Boundary: - Directional (one-tailed) and non-directional (two-tailed) tests is not a universal recommendation. Check the syllabus scope, assumptions, units and the limits of the evidence before generalising.

2.2.5 Experimental and research designs: repeated measures, independent groups and matched pairs, the issues with each and possible controls.

Use - experimental and research designs to connect the rule to the data and decision in the question.

This matters because - experimental and research designs determines what can be inferred or chosen; begin with the stated conditions and keep the conclusion tied to the evidence.

Example: apply - experimental and research designs to one small, clearly defined case, show the key step or comparison, and explain the result in words.

Boundary: - Experimental and research designs is not a universal recommendation. Check the syllabus scope, assumptions, units and the limits of the evidence before generalising.

2.2.6 Operationalisation of variables, extraneous variables and confounding variables.

Use - operationalisation and variables to connect the rule to the data and decision in the question.

This matters because - operationalisation and variables determines what can be inferred or chosen; begin with the stated conditions and keep the conclusion tied to the evidence.

Example: apply - operationalisation and variables to one small, clearly defined case, show the key step or comparison, and explain the result in words.

Boundary: - Operationalisation and variables is not a universal recommendation. Check the syllabus scope, assumptions, units and the limits of the evidence before generalising.

2.2.7 The use of control groups, counterbalancing, randomisation and order effects.

Use - control groups and order controls to connect the rule to the data and decision in the question.

This matters because - control groups and order controls determines what can be inferred or chosen; begin with the stated conditions and keep the conclusion tied to the evidence.

Example: apply - control groups and order controls to one small, clearly defined case, show the key step or comparison, and explain the result in words.

Boundary: - Control groups and order controls is not a universal recommendation. Check the syllabus scope, assumptions, units and the limits of the evidence before generalising.

2.2.8 Situational and participant variables.

Use - situational and participant variables to connect the rule to the data and decision in the question.

This matters because - situational and participant variables determines what can be inferred or chosen; begin with the stated conditions and keep the conclusion tied to the evidence.

Example: apply - situational and participant variables to one small, clearly defined case, show the key step or comparison, and explain the result in words.

Boundary: - Situational and participant variables is not a universal recommendation. Check the syllabus scope, assumptions, units and the limits of the evidence before generalising.

2.2.9 Objectivity, reliability and validity (internal, predictive and ecological).

Use - objectivity, reliability and validity to connect the rule to the data and decision in the question.

This matters because - objectivity, reliability and validity determines what can be inferred or chosen; begin with the stated conditions and keep the conclusion tied to the evidence.

Example: apply - objectivity, reliability and validity to one small, clearly defined case, show the key step or comparison, and explain the result in words.

Boundary: - Objectivity, reliability and validity is not a universal recommendation. Check the syllabus scope, assumptions, units and the limits of the evidence before generalising.

2.2.10 Experimenter effects, demand characteristics and control issues.

Use - experimenter effects and demand characteristics to connect the rule to the data and decision in the question.

This matters because - experimenter effects and demand characteristics determines what can be inferred or chosen; begin with the stated conditions and keep the conclusion tied to the evidence.

Example: apply - experimenter effects and demand characteristics to one small, clearly defined case, show the key step or comparison, and explain the result in words.

Boundary: - Experimenter effects and demand characteristics is not a universal recommendation. Check the syllabus scope, assumptions, units and the limits of the evidence before generalising.

2.2.11 List A from Topic A. 18.

Use - list a quantitative and qualitative data to connect the rule to the data and decision in the question.

This matters because - list a quantitative and qualitative data determines what can be inferred or chosen; begin with the stated conditions and keep the conclusion tied to the evidence.

Example: apply - list a quantitative and qualitative data to one small, clearly defined case, show the key step or comparison, and explain the result in words.

Boundary: - List A quantitative and qualitative data is not a universal recommendation. Check the syllabus scope, assumptions, units and the limits of the evidence before generalising.

2.2.12 (List B) Decision making and interpretation of inferential statistics:.; levels of measurement.; Wilcoxon signed ranks test of difference (also covering Spearman's rank correlation coefficient (formula) and Spearman's rank (critical values table) and Chi-squared distribution once Unit 2 has been covered).; probability and levels of significance (p≤.10 p≤.05 p≤.01).; observed and critical values, and sense checking of data.; one- or two-tailed regarding inferential testing.; type I and type II errors.

Use - inferential statistics decisions to connect the rule to the data and decision in the question.

This matters because - inferential statistics decisions determines what can be inferred or chosen; begin with the stated conditions and keep the conclusion tied to the evidence.

Example: apply - inferential statistics decisions to one small, clearly defined case, show the key step or comparison, and explain the result in words.

Boundary: - Inferential statistics decisions is not a universal recommendation. Check the syllabus scope, assumptions, units and the limits of the evidence before generalising.

2.2.13 Case studies of brain-damaged patients related to research into memory, including the case of Henry Molaison (HM).

Use - case studies of brain-damaged patients to connect the rule to the data and decision in the question.

This matters because - case studies of brain-damaged patients determines what can be inferred or chosen; begin with the stated conditions and keep the conclusion tied to the evidence.

Example: apply - case studies of brain-damaged patients to one small, clearly defined case, show the key step or comparison, and explain the result in words.

Boundary: - Case studies of brain-damaged patients is not a universal recommendation. Check the syllabus scope, assumptions, units and the limits of the evidence before generalising.

2.3.1 Bartlett (1932) War of the Ghosts.; Contemporary study.

Use - bartlett (1932) war of the ghosts to connect the rule to the data and decision in the question.

This matters because - bartlett (1932) war of the ghosts determines what can be inferred or chosen; begin with the stated conditions and keep the conclusion tied to the evidence.

Example: apply - bartlett (1932) war of the ghosts to one small, clearly defined case, show the key step or comparison, and explain the result in words.

Boundary: - Bartlett (1932) War of the Ghosts is not a universal recommendation. Check the syllabus scope, assumptions, units and the limits of the evidence before generalising.

2.3.2 Schmolck et al. (2002) Semantic knowledge in patient HM and other patients with bilateral medial and lateral temporal lobe lesions.; One contemporary study from the following two choices:.

Use - schmolck et al. (2002) patient hm to connect the rule to the data and decision in the question.

This matters because - schmolck et al. (2002) patient hm determines what can be inferred or chosen; begin with the stated conditions and keep the conclusion tied to the evidence.

Example: apply - schmolck et al. (2002) patient hm to one small, clearly defined case, show the key step or comparison, and explain the result in words.

Boundary: - Schmolck et al. (2002) patient HM is not a universal recommendation. Check the syllabus scope, assumptions, units and the limits of the evidence before generalising.

2.3.3 Darling et al. (2007) Behavioural evidence for separating components within visuo-spatial working memory.

Use - darling et al. (2007) visuospatial working memory to connect the rule to the data and decision in the question.

This matters because - darling et al. (2007) visuospatial working memory determines what can be inferred or chosen; begin with the stated conditions and keep the conclusion tied to the evidence.

Example: apply - darling et al. (2007) visuospatial working memory to one small, clearly defined case, show the key step or comparison, and explain the result in words.

Boundary: - Darling et al. (2007) visuospatial working memory is not a universal recommendation. Check the syllabus scope, assumptions, units and the limits of the evidence before generalising.

2.3.4 Sacchi et al. (2007) Changing history: doctored photographs affect memory for past public events.

Use - sacchi et al. (2007) doctored photographs and memory to connect the rule to the data and decision in the question.

This matters because - sacchi et al. (2007) doctored photographs and memory determines what can be inferred or chosen; begin with the stated conditions and keep the conclusion tied to the evidence.

Example: apply - sacchi et al. (2007) doctored photographs and memory to one small, clearly defined case, show the key step or comparison, and explain the result in words.

Boundary: - Sacchi et al. (2007) doctored photographs and memory is not a universal recommendation. Check the syllabus scope, assumptions, units and the limits of the evidence before generalising.

Conduct one ethical cognitive-psychology practical: design a repeated-measures laboratory experiment that gathers quantitative data. Make decisions about sampling, operationalisation, controls, hypotheses, experimenter effects, demand characteristics and order effects. Present and interpret central tendency, dispersion and appropriate graphs; consider normality where relevant; use the Wilcoxon non-parametric test of difference with significance and critical/observed values; evaluate strengths, weaknesses and improvements; and write the procedure, results and discussion. Suitable contexts include dual-task working-memory studies or acoustic similarity and short-term memory.

Use - cognitive psychology practical investigation to connect the rule to the data and decision in the question.

This matters because - cognitive psychology practical investigation determines what can be inferred or chosen; begin with the stated conditions and keep the conclusion tied to the evidence.

Example: apply - cognitive psychology practical investigation to one small, clearly defined case, show the key step or comparison, and explain the result in words.

Boundary: - Cognitive psychology practical investigation is not a universal recommendation. Check the syllabus scope, assumptions, units and the limits of the evidence before generalising.