Changes for page Measuring Instruments

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7	7	- What are the high-level goals? Who wants it and why? The goals influence the approach of the study
8	8
9	9	**E**xplore the questions
	10	+- Define the goals and reseach questions
10	10
11	11	**C**hoose evaluation approach and methods
	13	+- Influences the data collection, analysis and presentation
	14	+- Exploratory research => qualitative data, observational study,
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13	13	**I**dentify practical issues
	17	+- Users, budget, schedule, equipment etc.
	18	+- Pilot study important
14	14
15	15	**D**ecide about ethical issues
	21	+- Adhere to ethical procedure
	22	+- User rights! Explain the goals (before/after), methodology etc.
16	16
17	17	**E**valuate, analyze, interpret, present data
	25	+- Reliable results: Can the results be replicated?
	26	+- Validity: Is the data related to the hypothesis?
	27	+- Bias: Are the results unbiased?
	28	+- Scope: Can this be generalised?
	29	+- Ecological validity: Is the environment influencing the results?
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	31	+== IMPACT ==
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	33	+**I**ntention: Present the objectives and claims
	34	+
	35	+**M**easures and metrics: "What, how and why"
	36	+
	37	+**P**eople: Define the participants
	38	+
	39	+**A**ctivities: Use cases into activities
	40	+
	41	+**C**ontext: Social, ethical, physical, etc. environment definition
	42	+
	43	+**T**echnologies: Hardware and software
	44	+
	45	+
	46	+= Evaluation methods =
	47	+
	48	+== Formative evaluation ==
	49	+
	50	+- Open ended evaluation on the design
	51	+- E.g. How will the users respond to the new design?
	52	+
	53	+
	54	+== Summative evaluation ==
	55	+
	56	+- Focus on the overall effect
	57	+- Summarizes if the objective is reached
	58	+- E.g. Are the participants happier when working with design X in comparison to design Y?
	59	+
	60	+== Data ==
	61	+
	62	+- Qualitative: Explore, discover, instruct
	63	+
	64	+- Quantitative: Describe, explain, predict
	65	+
	66	+ - Subjective quantitative
	67	+
	68	+
	69	+== Statistics ==
	70	+
	71	+- Descriptive: Describe the dataset, e.g. mean time on task
	72	+- Inferential: Using a sample to infer about a population, e.g. predicted mean time on task based on user characteristics.
	73	+
	74	+== Experiment Design: Conditions ==
	75	+
	76	+=== Within Subjects (Repeated Measures) ===
	77	+Each participant is subjected to all the test conditions.
	78	+Fewer subjects needed and reduces variance in the Can be difficult to setup due to subjects fatiguing, learning about the setup or simply not having enough time.
	79	+
	80	+=== Between Subjects (Between Groups) ===
	81	+One subject undergoes only one test. Simple to execute, but results in significant variance due to inter-subject differences in characteristics.
	82	+
	83	+
	84	+