2Components of the Research Proposal Problem Description/StatementResearch ObjectivesImportance/Benefits of the StudyLiterature ReviewResearch Design / Data AnalysisDeliverablesSchedule[Facilities and Special Resources]ReferencesBudget (Appendix)
3Problem StatementReview the discussion from Week 2 on problem statements.
4Purpose of the Problem Statement Represents the reasons/motivation behind your proposal (based on the specific domain of study).It specifies the conditions you want to change or the gaps in existing knowledge you intend to fill (this is the specification of the research problem).Should be supported by evidence.Specifies your hypothesis that suggests a solution to the problem.Shows your familiarity with prior research on the topic and why it needs to be extended.Even if the problem is obvious, your reviewers want to know how clearly you can state it.
5Guidelines for writing a good abstract/problem statement All should have the following elements in this order:State the general case / problemDescribe what others have doneWhat’s missing / where is the gap in knowledge?Describe the proposed solution or research objectives/questionsSpecify one or more specific hypothesesShould include specific metrics/measurementsDiscuss how their validation addresses the research questionsSpecific results (or research design, if it is a proposal)
6Purpose of the Research Objectives Section Specify the outcome of your project, the end product(s)Keep you objectivesSpecific: indicate precisely what you intend to change through your projectMeasurable –what you accept as proof of project successLogical – how each objective contributes to systematically to achieving your overall goal
7Research Objectives Flows naturally from the problem statement state your hypotheses clearlygive the reader a concrete, achievable goalVerify the consistency of the proposalcheck to see that each objective is discussed in the research design, data analysis and results sections
8Literature Review Recent or historically significant research studies Always refer to the original sourceDiscuss how the literature applies, show the weaknesses in the design, discuss how you would avoid similar problemsHow is your idea different/better?
9Importance/Benefits of the Study Importance of the doing the study nowWhat are the potential impacts onResearch in the areaApplications of the research if successfulBroader impact (in other areas, on the society, in education, etc.)If you find this difficult to write, then most likely you have not understood the problem
10Research Design What you are going to do in technical terms. May contain many subsectionsBe specific about what research methodology you will use and whyProvide details of your proposed solutions to the problem and sub-problemsProvide information for tasks such as sample selection, data collection, instrumentation, validation, procedures, ethical requirements
11Schedule & Deliverables Include the major phases of the projectexploratory studies, data analysis, report generationCritical Path Method (CPM) of scheduling may helpDeliverables:Measurement instrumentsAlgorithmsComputer programs / prototypesComparative evaluationOther technical reports
12Budget and Resources Itemized Budget Provide a Budget Narrative Access to special systems or computersInfrastructure needsCosts of surveys, user studies, etc.Cost of travel if related to research designProvide a Budget NarrativeThis part is usually an appendix.
13Proposal Characteristics Straightforward documentNo extraneous or irreverent materialDon’t tell us why you became interested in the topicThe first words you write are the most important onesNot a literary productionClear, sharp and preciseeconomy of words; no rambling sentencesClearly organizedOutlined with proper use of headings and subheadings
14Suggested Organization Title, Abstract, Keywords (problem statement)Introduction and OverviewBackground information; problem description in contextHypotheses and objectivesAssumptions and delimitationsImportance and benefitsRelated Work/Literature ReviewResearch Design and MethodologyPlan of Work and Outcomes (deliverables, schedule)Conclusions and Future WorkReferencesBudget (appendix)
15Weaknesses in Research Proposals Research Problemunfocusedunimportant (done before!)more complexlimited relevance
16Weaknesses in Research Proposals Research Designso vague it prevents evaluationinappropriate or impossible dataprocedures inappropriate for problemThreats to validityLack of reliable measureslacking controls
17A Sample Research Proposal Read (and study) the sample proposal in Chapter 5 of in Practical ResearchFill in the critique in Chapter 12 for this proposal.Since the critique is designed for a REPORT, simply change the tense for most questions.Is the sample size adequate? -> Will the sample size be adequate
195 Key Questions to Answer in Your Problem Statement Does your problem statement:Demonstrate a precise understanding of the problem you are attempting to solve?Clearly convey the focus of your project early in the narrative?Indicate the relationship of your project to a larger set of problems and justify why your particular focus has been chosen?Demonstrate that your problem is feasible to solve?Make others what to read it further?
205 Key Questions to Answer for Purpose and Objectives Does this sectionClearly describe your project’s objective, hypotheses and/or research question?Bury them in a morass of narrative?Demonstrate that your objectives are important, significant and timely?Include objectives that comprehensively describe the intended outcomes of the project?State objectives, hypothesis or questions in a way they can be evaluated or tested later
21Writing Tips for Objectives Section Don’t confuse your objectives (ends) with you methods (means).A good objective emphasizes what will be done, whereas a method will explain why or how it will be done.Include goals (ultimate) and objectives (immediate)
22Purpose of the Research Design Describes your project activities in detailIndicates how your objective will be accomplishedDescription should include the sequence, flow, and interrelationship of activitiesIt should discuss the risks of your method, and indicate why your success is probableRelate what is unique about your approach.
23Data Analysis Data Analysis is essentially a four step process Identify precisely what will be evaluated. If you wrote measurable objectives, you already know.Determine the methods used to evaluate each objective. More precisely, you will need to describe the information you will need and how you propose to collect it.3. Specify the analyses you plan to make and the data you need to collect. Your design may be simply to observe behavior of a particular population or something more complex like a rigorous experimental and multiple control group design.4. Summarize the resulting data analyses and indicate its use. Consider mock data tables that show what your resulting data might look like.
24Key Questions to Answer for Research Design/Data Analysis Does the research design and data analysis sectionDescribe why analysis is needed in the project?Clearly identify the purpose of your analysis?Demonstrate that an appropriate analysis procedure is included for each project objectiveProvide a general organizational plan or model?Demonstrate what information will be needed to complete the analysis, the potential sources and the instruments that will be used to collect it.
25Writing Tips for Research Design Begin with your objectivesDescribe the precise steps you will follow to carry out each objective, including what will be done, and who will do it.Keep asking and answering the “What’s next?” question.Once you have determined the sequence of events, cast the major milestones into a time-and-task chart
26Scientific Writing Prosaic Clear, accurate, but not dull Economy – every sentence necessary but not to the point of over condensingEgo less – you are writing for the readers not yourself
27Scientific Tone Objective and accurate To inform not entertain Do not over qualify – modify every claim with caveats and cautionsNever use idioms like “crop up”, “loose track”, “it turned out that”, etc.Use examples if they aid in clarification
28Scientific Motivation Brief summaries at the beginning and end of each sectionThe connection between one paragraph and the next should be obviousMake sure your reader has sufficient knowledge to understand what follows
29Other Writing IssuesThe upper hand – inclusion of offhanded remarks like “ …this is a straightforward application …”Obfuscation – aim is to give an impression of having done something without actually claiming to have done itAnalogies – only worthwhile if it significantly reduces the work of understanding, most of the time bad analogies lead the reader astray
30Writing IssuesStraw men – indefensible hypothesis posed for the sole purpose of being demolished“it can be argued that databases do not require indexes”Also use to contrast a new idea with some impossibly bad alternative, to put the new idea in a favorable light
31Unsubstantiated Claims Example:Most user prefer the graphical style of interface.We believe that ….ExampleAnother possibility would be a disk-based method, but this approach is unlikely to be successful.Another …, but our experience suggests that …
32References and Citation Up-to-dateRelevant (no padding)Original sourceFirst order: books and journal articlesSecond order: conference articleThird order: technical reportNo private communications or forums ( material cannot be accessed or verified) if you must leave as a footnote not in the bibliographyDo not cite support for common knowledge
33Reference and Citation Carefully relate your new work to existing work, show how your work builds on previous knowledge, and how it differs from other relevant results.References – demonstrate the claims of new, knowledge of the research area, pointers to background reading
34Citation Style References should not be anonymous Other work  -> Marsden  has …In self-references, readers should know that you are using yourself to support your argument not independent authoritiesAvoid unnecessary discussion of references, Several authors …., we cite …
35Citation styleOrdinal-number style, name-and-date style, superscripted ordinal numbers, and strings.Use anyone, but use one!Entries orderedBy appearance of citationalphabetically
36Quotation Text from another source If short – enclosed in double quotesIf long – set aside in an indented blockLong quotations, full material, algorithms, figures may require permission from the publisher and from the author of the originalUse of quotes for other reasons is not recommended
37Acknowledgements Anyone who made a contribution Advice, proofreading, technical support, funding resourcesDon’t list your family, unless they really contributed to the scientific contents
38Ethics Don’t Present opinions as fact Distort truths Plagiarize Imply that previously published results are originalPapers available on the internet – authors put out an informal publication and becomes accepted as a formal. It is expected that the informal version will be removed
39Notes on Research Design You have decidedWhat the problem isWhat the study goals areWhy it is important for you to do the studyNow you will construct the research design which describes what you are going to do in technical terms.
41Research DesignIs a plan for selecting the sources and types of information used to answer the research question.Is a framework for specifying the relationships among the study’s variablesIs a blueprint that outlines each procedure from the hypothesis to the analysis of data.
42Research DesignThe research design will provide information for tasks such asSample selection and sizeData collection methodInstrumentationProceduresEthical requirementsRejected alternative designs
43Classification of Research Designs Exploratory or formalObservational or communication basedExperimental or ex post factoDescriptive or causalCross-sectional or longitudinalCase or statistical studyField, laboratory or simulation
44Exploratory or FormalExploratory studies tend toward loose structures with the objective of discovering future research tasksGoal - to develop hypotheses or questions for further researchFormal study begins where the exploration leaves off and begins with the hypothesis or research questionGoal – test the hypothesis or answer the research question posed
45Observational or Communication Based Observational studies – the researcher inspects the activities of a subject or the nature of some material without attempting elicit responses from anyone.Communicational – the researcher questions the subjects and collects response by personal or impersonal means.
46Experimental or Ex Post Facto In an experiment the researcher attempts to control and/or manipulate the variables in the study. Experimentation provides the most powerful support possible for a hypothesis of causationWith an ex post facto design, investigators have no control over the variables in the sense of being able to manipulate them. Report only what has happened or what is happening. Important that researches do not influence variables
47Descriptive or CausalIf the research is concerned with finding out who, what, where, when or how much then the study is descriptive.If is concerned with finding out why then it is causal. How one variable produces changes in another.
48Cross-sectional or Longitudinal Cross-sectional are carried out once and represent a snapshot of one point in time.Longitudinal are repeated over an extended period
49Case or Statistical Study Statistical studies are designed for breath rather than depth. They attempt to capture a population’s characteristics by making inference from a sample’s characteristics.Case studies – full contextual analysis of fewer events or conditions and their interrelations. (Remember that a universal can be falsified by a single counter-instance)
50Field, Laboratory or Simulation Designs differ in the actual environmental conditions
51Quantitative v. Qualitative Approaches Categorize research studies into two broad categoriesQuantitative – relationships among measured variable for the purpose of explaining, predicting and controlling phenomenaQualitative – answer question about the complex nature of phenomena with the purpose of describing and understanding from the participant’s point of view
52The Validity of Your Method Accuracy, meaningfulness, an credibilityMost important questions:Does the study have sufficient controls to ensure that the conclusions we draw are truly warranted by the data? (internal validity)Can we use what we have observed in the research situation to make generalizations about the world beyond that specific situation? (external validity)
53Strategies to reduce internal validity problems Controlled laboratory studyA double-blind experimentUnobtrusive measures ( to see where people use the library look at worn flooring)Triangulation – multiple sources
54Strategies to enhance external validity A real-life setting – artificial settings may be quite dissimilar from real-life circumstancesRepresentative sampleReplication in a different context
55Formal Notion of Validity “The best available approximation to the truth of a given proposition, inference, or conclusion”Source: Research Methods Knowledgebase
56Types of Validity Conclusion Validity: Construct Validity: Is there a relationship between the two variables?Internal Validity:Assuming that there is a relationship, is it a causal one?Construct Validity:Assuming that there is a causal relationship, can we claim that the program reflected our construct of the program and that our measure reflected well our idea of the construct of the measure?External Validity:Can we generalize the (causal) effect to other settings, domains, persons, places or times?
57Types of ValiditySource: Research Methods Knowledgebase
59Setting of the Problem Statement of the Problem Goal Establishes Additional information to comprehend fully the meaning of the problemhypothesisscopedefinitionsassumptions
60Hypotheses Tentative proposition formulated for empirical testing Means for guiding and directingkinds of data to be collectedanalysis and interpretationhave nothing to do with proofacceptance or rejection is dependant on “data”
61Examples of Hypotheses Error-based pruning reduces the size of decision trees (as measured in the number of nodes) without decreasing accuracy (as measured by error rate)The use of relevance feedback in an information retrieval system, results in more effective information discovery by users (as measured in terms of time to task completion)The proposed approach for generating item recommendations based on association rule discovery on purchase histories results in more accurate predictions of future purchases when compared to the baseline approach.[From a recent Google experiment] Longer documents tend to be ranked more accurately than shorter documents because their topics can be estimated with lower variance.
62Rejecting the Hypothesis Often researchers set out to disprove an opposite/competing hypothesisExample: We believe that test strategy A uncovers more faults than test strategy B. So our hypothesis will be thatProgrammers using test strategy A will uncover more faults than programmers using test strategy B for the same program.
63Rejecting the Hypothesis However, we cannot actually prove this hypothesis, we instead will try to disprove an opposite hypothesisThere will be no difference in the fault detection rate of programmers using test strategy A and those using test strategy B for the same program.
64Types of Hypotheses Existential Compositional An entity or phenomenon exists (perhaps with a specified frequency)“Atoms contain uncharged subatomic particles (neutrons)”CompositionalAn entity or phenomenon consists of a number of related parts or components (perhaps with a specified frequency)“Atoms consist of proton, electrons, and neutrons.”“All decision tree algorithms can be divided into a growing phase and a pruning phase.”
65Types of Hypotheses Correlational Casual Two measurable quantities have a specified association“An element’s atomic weight and its properties are correlated.”“The size of a decision tree constructed using error-based pruning grows linearly with the size of training set.”CasualA given behavior has a specified causal mechanism“The low reactivity of noble gases is caused by their full outer shell of valence electrons.”“The use of relevance feedback results in more effective information discovery by users”
66Rejecting the Hypothesis If there is a significant difference in the fault detection rate we can reject the “no difference” and by default, support our research hypothesisthe “no difference” = null hypothesis
67Recall: Falsifiability Falsifiability is the logical possibility that an assertion can be shown to be false by evidenceDoes not mean “false.” Instead, if a falsifiable proposition is false, its falsehood can be shown by experimentation, proof, or simulation.There are different degrees of falsifiabilityWhat make a hypothesis unfalsifiable?Vagueness – theory does not predict any particular experimental outcomeComplexity/Generality – theory “explains” any experimental resultSpecial pleading – traditional experimental methods are claimed not to apply
68Delimiting the Research This is what the researcher does not want to do in the projectShould be stated clearly and explicitly.What will be done is part of the problem statement.
69ExperimentsStudies involving the intervention by the researcher beyond that required for measurementusually, manipulate some variable in a setting and observe how it affects the subject (cause and effect)there is at least one independent variable and one dependent variable
70Independent Variable Variable the researcher manipulates For our hypothesis concerning test strategies, we may take a sample of software engineers and randomly assign each to one of two groups: one using test strategy A and the other test strategy B. Later we compare the fault detection rate in the two groups.We are manipulating the test strategy, thus it is the independent variable
71Dependent VariableVariable that is potentially influenced by the independent variablein our last example, the dependent variable is fault detection ratePresumably the fault detection rate is influenced by test strategy appliedthere can be more than one dependent variable
72Conducting an Experiment Seven activitiesselect relevant variablesspecify the level(s) of treatmentcontrol the experimental environmentchoose the experimental designselect and assign the subjectspilot-test, revise, and testanalyze the data
73Select the Relevant Variables Translate our problem into the hypothesis that best states the objectives of the researchhow concepts are transformed into variables to make them measurable and subject to testingresearch question:Does a product presentation that describes product benefits in the introduction lead to improved retention of the product knowledge?
74The SpeculationProduct presentations in which the benefits module is placed in the introduction of a 12 minute message produce better retention of product knowledge that those where the benefits module is placed in the conclusion.
75Researcher’s Challenge Select variables that are the best operational representations of the original concepts.Sales presentation, product benefits retention, product knowledgeDetermine how many variables to testconstrained by budget, the time allocated, the availability of appropriate controls, and the number of subjects
76Researcher’s Challenge Select or design appropriate measures/metrics for themthorough review of the available literature and instruments.Adapted to unique needs of the research situation
77Choosing an Experimental Design Experimental designs are unique to the experimental methodstatistical plans to designate relationships between experimental treatments and the experimenter’s observationsimprove the probability that the observed change in the dependent variable was caused by the manipulation of the independent variable
78Validity in Measurements Validity: the extend to which instrument measures what is supposed to be measuredE.g., thermometer temperatureE.g., IQ Test Intelligence?E.g., CPU time algorithm complexity or efficiency
79Reliability of Measurement Reliability: accuracy and consistency by which the instrument can perform measurementAccuracy exists only if there is consistency (not necessarily the other way around)Need to measure more than onceReliability is a necessary but not sufficient condition for validity