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
11	11
12	12	**C**hoose evaluation approach and methods
13		-- Influences the data collection, analysis and presentation
14		-- Exploratory research => qualitative data, observational study,
15	15
16	16	**I**dentify practical issues
17		-- Users, budget, schedule, equipment etc.
18		-- Pilot study important
19	19
20	20	**D**ecide about ethical issues
21		-- Adhere to ethical procedure
22		-- User rights! Explain the goals (before/after), methodology etc.
23	23
24	24	**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?
30	30
31		-== IMPACT ==
32	32
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		-