forskningsmetoder

All None Speichern

• implicit knowledge informal, in-head
• explicit knowledge formal, documents, databases
• descriptive/categorial knowledge most fundamental, describe phenomen with its characteristics
• explanation/declarative knowledge why a phenomen is in a certain way, cause-effect-relation explained
• evaluation/value knowledge knowledge about desired - given specific circumstances, goals
• normative/prescriptive knowledge guiding knowledge, instructions
• positivism how reality is! highly structured, quantifiable observations that lend to statistical analysis, complexity reduced to generalization
• realism object exist independently of our will & knowledge
• pragmatism focus on the practical consequenses of actions, if concept works in practise - it is considered true
• Interpretation & hermeneutics to understand phenomens from another person's perspective
• Induction start observe, then theory
• deduction start with theory, then validation/proof
• action research consult, support practise, tech in social context
• design science research response to an it problem, artifact, new solutions
• technical action research tech-driven, solve a lot of problems, designer, helper, researcher
• what is good research orginality, reliability, communication, relevance, rigor
• why literature review need to know what has been solved in order to motivate research gap
• literature process define topic, limit search, test search, review results, conduct search, manage results, evaluate results, report
• systematic literature review focused on gathering evidence and resolve validity threats
• bad literature review lack of focus, organization, depth, bad sources, exist research
• survey purpose collect data from a large sample of respondents
• survey steps define variables to measure, develop questions, validate
• piloting distribute survey to a small set of respondents
• stratified sampling practical random approach, sub-groups based on criterias such as age, gender
• confirmation bias agree rather than disagree
• when should we use experiments need to identify dependable relationship between cause & effect
• casual relationship when the cause precedes/relates to the effect
• independent variable cause, variable manipulated under experiment
• dependent variable effect, depends on the independent variable
• hypothesis precise problem statement that could be tested
• confounding variable not controlled but can affect outcome
• control variable not under investigation, kept constant, font size
• within-subjects each p tested on each condition
• between-subjects each p tested on one condition only
• replication repetition of entire experiment
• purpose statistic analyze if our results is accurate
• confidence interval maesure of how confident we are in our results
• Inferential statistics how we draw conclusions from data - correlation, hypothesis
• data level determines what type of measurements & procedures we can apply
• nominal data categorial data with no meaningful distance, animal
• nominal data descriptives frequencies & percentages, mode
• ordinal data ordered data with undefined length between steps, tasty
• ordinal descriptives frequencies & percentages, median
• interval & ratio equal distance between steps, parametric
• interval & ratio descriptives mean, standard deviation
• mean medelvärde
• standard deviation hur spridda värdena är runt medelvärdet
• hypothesis testing goal to determine if we can reject null hypothesis in favor of the one we defined
• statistically significance - hypothesis testing acheived when a result is very unlikely given the null hypothesis is true
• p-value p under a = s results - reject null
• t-test one sample if mean of one sample is different from reference value
• t-test independent sample test if the mean of one sample is different from mean of another independent sample
• t-test paired sample test if the mean of 2 measures from the same sample differs
• normal distribution test curves, 0,05
• rank-sum test independent variables, ranking indicidual measures, ordinal data
• sign test positive of negative 2 measures
• CHI2 test if frequency of observation is different from some reference frequency, between groups
• correlation variables affect each other
• positive correlation both increase
• quantitative analysis checklist 1. interpret which data levels 2. descriptives 3. identify test, h c 4. apply tests
• purpose of academic knowledge contribute to scientific knowledge
• academic paper structure 1. introduction 2. method 3. result 4. discussion 5. conclusion
• good scientific practices correct sample, reference, grounding related work
• scientific evaluation bias, reliability, validity

All None Speichern