Assessment Brief

Pleasetakethetimetothoroughlyreadthisassessmentbrief.Itoutlinesthemethodsofassessment, deadlines for submissions, and details on when you will receive your grades and feedback.

Learning Outcomes

• Thisassessmentwillfullyassessthefollowing5learningoutcomesforthismodule:

• <!-- [if !supportLists]-->Summarisenumericaldatainavarietyofgraphicalforms.

• <!-- [if !supportLists]-->Differentiatebetweenthevariousanalyticaltechniquesforsolvingbusinessproblems.

• <!-- [if !supportLists]-->Illustratetheimportanceofstatingassumptions.

• <!-- [if !supportLists]-->ManipulatedatausingExcel.

• <!-- [if !supportLists]-->Interpretdatainordertodevelopandtestclaims.

SummativeAssessment:

This module is assessed by one component worth 100% of the module mark. You will produce an individual written report and an accompanying Excel workbook, applying quantitative and data- drivenmethodstohelpLSBUBusinessSchoolenhancestudentslearningexperiencesandimprove their outcomes.

Youwillchooseoneofthefollowingfive(5)topics,usingitasthefoundationforyouranalysesand recommended actions:

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1.

<!--[endif]-->ArtificialIntelligence,AugmentedReality,andGamification,examplesinclude:

• <!-- [if !supportLists]-->DesigningInnovativeLearningSpaceswiththeMetaverse

• <!-- [if !supportLists]-->RedefiningAssessmentandFeedbackPracticeswithGenerativeAI

• <!-- [if !supportLists]-->EnhancingEngagementThroughGamifiedLearningExperiences

<!--[endif]-->CreatingImmersiveandCollaborativeLearningExperienceswithAugmentedReality

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2.

<!--[endif]-->PromotingaCultureofDiversityandInclusivity,examplesinclude:

• <!-- [if !supportLists]-->BuildingInclusiveCampusCommunities

• <!-- [if !supportLists]-->CreatingaDiverseandRepresentativeCurriculum

• <!-- [if !supportLists]-->ProvidingAccessibleStudyMaterials,CourseworkandTailoredFeedback

• <!-- [if !supportLists]-->Theimpactofadiversebodyofstudentsinclassroomonthelearningexperience

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3.

<!--[endif]-->AwarenessofCareerChoicesandStudentSupport,examplesinclude:

• <!-- [if !supportLists]-->ProvidingCoaching,Mentoring,andPersonalTutoring

• <!-- [if !supportLists]-->LeveragingUniversityCareerCentresandPlacementSchemes

• <!-- [if !supportLists]-->StressingtheImportanceofGradesandFeedback

• <!-- [if !supportLists]-->SupportingNetworkingOpportunitiesandIndustryConnections

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4.

<!--[endif]-->ExploringLearningStylesandModes:EnhancingAcademicAccessibility,examplesinclude:

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o

<!--[endif]-->UnderstandingVisual,Auditory,andOtherLearningStyles

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o

<!--[endif]-->LeveragingOnline,Onsite,andHybridLearningModes

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o

<!--[endif]-->DesigningPersonalisedFeedbackandGradingSystemsforIndividualSuccess

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o

<!--[endif]-->ImplementingOnline,Onsite,andHybridLearningforGreaterAccessibility

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5.

<!--[endif]-->StudentWellbeingandMentalHealthinHigherEducation,examplesinclude:

• <!-- [if !supportLists]-->ProvidingAdequateMentalHealthSupportandResources

• <!-- [if !supportLists]-->MeasuringtheImpactofWellbeingProgramsonAcademicPerformance

• <!-- [if !supportLists]-->PromotingaHealthyAcademicEnvironment

• <!-- [if !supportLists]-->Theimpactofsocialmediaonwell-beingofstudents

YourTasks:

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1.

<!--[endif]-->InvestigateLatestTrendsandChallengesinHigherEducationthatappliestoLSBU

Conduct background research on your chosen topic, focusing on current developments and challengesinHigherEducation(bothintheUKandglobally).Summarizeyourfindingstohighlight the primary issues LSBU Business School may face.

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2.

<!--[endif]-->ProposeData DrivenSolutions&ConstructSpeculations(Claims)

Basedonyourpreliminaryresearch,proposedata-drivenideasorsolutionstoaddresstheidentified challenges.Then, formspeculations (claims)abouthowthese solutionsmightimpactLSBUBusiness School students learning experience, motivation, or academic outcomes.

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3.

<!--[endif]-->DesignaSurveyandCollectData

• <!-- [if !supportLists]-->Questionnaire:Develop a short, well-structured survey to measure students perceptions,opinions,orattitudesregardingyourchosentopic.

• <!-- [if !supportLists]-->Ethics:Provide an ethics form ensuring informed consent, anonymity, and responsible data handling as per GDPR guidelines.

• <!-- [if !supportLists]-->DataCollection:Aimforaminimumof50validresponses,ensuringyourdatawillbe sufficiently diverse for statistical analysis.

• <!-- [if !supportLists]-->RawDataCheck:Validatethedatasetforduplicate,incomplete,orinconsistententriesand address these issues during preprocessing.

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4.

<!--[endif]-->QuantitativeAnalysisUsingExcel

Performdataanalysistotestyourspeculationsorclaims.Youareencouragedtousearange of quantitative methods, such as:

• • <!-- [if !supportLists]-->Descriptivestatistics(mean,median,mode,variance)

  • <!-- [if !supportLists]-->Exploratorydataanalysis(pivottables,frequencydistributions)

  • <!-- [if !supportLists]-->Basic inferential techniques (e.g., correlation, simple regression)

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    Data visualisation (charts, graphs, tables)

    Where appropriate, you may optionally use Python to perform advanced or automated analyses, though this is not mandatory. The emphasis is on clear, accurate, and relevant statistical methods.

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    5.

    <!--[endif]-->InterpretFindingsandMakeRecommendations

    • <!-- [if !supportLists]-->Summariseyourresultsclearly,providingvisualaids(charts,tables,infographics)were helpful.

    • <!-- [if !supportLists]-->Criticallydiscusshowthedatasupportsorcontradictsyourinitialspeculations.

    • <!-- [if !supportLists]-->Offerspecific,data-drivenrecommendationsfor LSBU Business Schools management,addressingfeasibility,scope,andpotentialimpactonstudentperformance.

    Assessment Criteria and Weighting:

    YoumustsubmittwofilesviaMoodle:

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    -

    <!--[endif]-->oneMSWorddocument(*.docx)and

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    <!--[endif]-->oneExcelworkbook(*.xlsx).

    Ensure each file is in the correct format, submitted before the deadline, and uploaded to the correct link.

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    1)

    <!--[endif]-->MSWordDocument(.docx)

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    <!--[endif]-->Thereportshouldbe1,800words(+/-10%)andincludeoneappendix.

    <!-- [if !supportLists]-->

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    <!--[endif]-->Yourappendixisnotincludedinthelimitofwordcount.

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    <!--[endif]-->DownloadthetemplatefromMoodle.

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    <!--[endif]-->Structure your discussion around six core areas, each tied to marks (total of 100 marks):

    • <!-- [if !supportLists]-->AimoftheReport&DataCollection (10marks)

    • <!-- [if !supportLists]-->DataAnalysisUsingExcel/Python (10marks)

    • <!-- [if !supportLists]-->DataRepresentation&Interpretation (10marks)

    • <!-- [if !supportLists]-->CommunicatingResults&ConclusionstoSchoolManagement (10marks)

    • <!-- [if !supportLists]-->EthicalConsiderations (5marks)

    • <!-- [if !supportLists]-->Academic Style (5 marks)

    AppendixAmustincludeyourlistofspeculations,questionnaire validMS FORMS link, and a signed ethics form. (10 marks)

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    2)

    <!--[endif]-->ExcelWorkbook(.xlsx)

    Organiseyourworkbookintofourworksheets,downloadthetemplatefromMoodle:

    • <!-- [if !supportLists]-->Sheet1:RawData (5marks)

    • <!-- [if !supportLists]-->Sheet2:Pre-processedData (10marks)

    • <!-- [if !supportLists]-->Sheet3:AnalysedData (15marks)

    • <!-- [if !supportLists]-->Sheet 4: Visualized & Interpreted Data (10 marks)

• Clearlylabel all charts, graphs, and tablesso the findingscan be connectedto yourwritten report. Students will need to apply concepts and technical skills learnt in lectures and workshops and develop analytical and criticalskillsinthecontextofdata-drivendecisionmaking.Thereportmusthave referenceswhichwillneed to be listed at the end. If you are not sure how to do this, you should check the information about LSBU Harvard Referencing style available on the Moodle site & MyAccount.

  Tosubmitthecoursework,studentsmustuploadtheir individualreport,asonewordfileandoneMSExcel workbook through the Submission link before 4PM on 6^th May 2025.

  Historyhasshownthatmanystudentsstruggletoformatandlocatetheirfilescorrectlyonthedeadlineday, oftenrushing andmakingmistakes. Therefore, itis highlyencouragedthat you submit your finalworkearly, preferably before 4 PM on Friday, 2nd May 2025. In order to pass this module, students must achieve a minimum mark of 40.

  FormativeAssessment:

  Formative feedback will be given during workshop sessions using practical activities. Feedback to students willbeprovidedastheyworkduringtheirworkshopsessions,tosupportthedevelopmentoftheirformative assessments.

  Thiswillinvolve:

  • <!-- [if !supportLists]-->In?classquestioningandquizzesduringthelectures&workshops.

  • <!-- [if !supportLists]-->Practicalbusinessexercises,discussionsandonlinequizzesduringtheworkshops.

  • <!-- [if !supportLists]-->Questionsandself?evaluationduringtheworkshop.

  • <!-- [if !supportLists]-->OnlineDrop-insessions,findthescheduleonyourtimetable.

  <!-- [if !supportLists]-->A timeline for the formative deadlines which will include feedback prior to submission in workshop from the workshop leader:

  1. <!-- [if !supportLists]-->week2:Choiceofassignmenttopic deadlineFriday7Feb4:00pm

  2. <!-- [if !supportLists]-->week4:QuestionnaireDesign deadlineFriday21Feb4:00pm

  3. <!-- [if !supportLists]-->week6:Datacollection deadlineFriday7March4:00pm

  4. <!-- [if !supportLists]-->week8:Pre-processedData deadlineFriday21March4:00pm

  5. <!-- [if !supportLists]-->week10:Pre-processed&AnalysedDatadeadlineFriday4April4:00pm

• Assessment Details:

  Type:	<!-- [if !supportLists]--> ? <!--[endif]-->Report/Portfolio(MSWord) <!-- [if !supportLists]--> ? <!--[endif]-->MSExcelworkbookwith4differentworksheets
  Resources:	<!-- [if !supportLists]--> ? <!--[endif]-->DDMMoodlecontents,Readinglist(books,podcasts,journalsand),LinkedIn Learning courses specified on Moodle site.
  WordCount:	<!-- [if !supportLists]--> <!--[endif]-->MSworddocument-1800words(+/?10%)+1Appendix <!-- [if !supportLists]--> <!--[endif]-->MSExcelworkbookwith4differentworksheets(nowordcount)
  Presentation:	<!-- [if !supportLists]--> <!--[endif]-->Workmustbereferenced,andabibliographyprovided. <!-- [if !supportLists]--> <!--[endif]-->WorkmustbesubmittedasoneWord(.docx)andoneExcel(xlsx)doc. <!-- [if !supportLists]--> <!--[endif]-->CourseworkmustbesubmittedusingCalibriorAptosfontsize11or12. <!-- [if !supportLists]--> <!--[endif]-->Yournamemustnotbeonyourcoursework.
  Referencing:	HarvardReferencingshouldbeused,seeyourLibrarySubjectGuideforguides and tips on referencing.
  Regulations:	MakesureyouunderstandtheUniversityPoliciesandProceduresonexpected academic practice and academic misconduct.Note in particular: <!-- [if !supportLists]--> <!--[endif]-->Your work must be your own. Markers will be attentive to both the plausibilityofthesourcesprovidedaswellastheconsistencyandapproach towritingofthework.Simply,ifyoudotheresearchandreading,andthen write it up on your own, giving the reference to sources, you will approach the work in the appropriate way and will cause not give markers reason to question the authenticity of the work. <!-- [if !supportLists]--> <!--[endif]-->Allquotationsmustbecreditedandproperlyreferenced.Paraphrasingisstill regarded as plagiarism if you fail to acknowledge the source for the ideas being expressed. TURNITIN:WhenyouuploadyourworktotheMoodlesiteitwillbecheckedby anti?plagiarismsoftware.

  Resources

  CoreReading:

  1. <!-- [if !supportLists]-->Evans,J.R.(2021).BusinessAnalytics,GlobalEdition.UnitedKingdom:PearsonHigherEducation& Professional Group.

  2. <!-- [if !supportLists]-->Priyadarsini,K.,Poongodi,B.,Latha,A.,Jaisankar,S.(2017).BusinessStatistics:WorkbookUsingExcel.India: Laxmi Publications.

  3. <!-- [if !supportLists]-->Sharda,R.,Delen,D.,Turban,E.,Liang,T.(2018).BusinessIntelligence,Analytics,andDataScience:AManagerial Perspective.United Kingdom: Pearson.

  4. <!-- [if !supportLists]-->Szabat,K.A.,Stephan,D.,Levine,D.M.(2020).BusinessStatistics:AFirstCourse. United Kingdom: Pearson

  5. Sharpe, N.D., De Veaux, R.D., Velleman, P.F. (2022).BusinessStatistics.4^th edition,NewYork:Pearson. Education International.

  6. <!-- [if !supportLists]-->Szabat, K. A., Berenson, M. L., Stephan, D., Levine, D. M. (2019).BasicBusinessStatistics,GlobalEdition. United Kingdom: Pearson.

• OptionalReading:

1. <!-- [if !supportLists]-->Camm,J.D.,Fry,M.J.,Cochran,J.J.,Ohlmann,J.W.(2021).BusinessAnalytics.UnitedStates:Cengage Learning.

2. <!-- [if !supportLists]-->Favero,L.P.,Belfiore,P.(2019).DataScienceforBusinessandDecisionMaking.UnitedKingdom: Elsevier Science.

3. <!-- [if !supportLists]-->Jackson,T.W.,Lockwood,S.(2018).BusinessAnalytics:AContemporaryApproach.UnitedKingdom: Bloomsbury Publishing.

4. <!-- [if !supportLists]-->Jain,P.,Sharma,P.,Jayaraman,L.(2014).BehindEveryGoodDecision:HowAnyoneCanUseBusinessAnalytics to Turn Data Into Profitable Insight.New York: American Management Association.

5. <!-- [if !supportLists]-->Nabavi,M.,Olson,D.L.,Boyce,W.S.(2020).IntroductiontoBusinessAnalytics,SecondEdition.United States: Business Expert Press.

6. <!-- [if !supportLists]-->Nelson,G.S.(2018).TheAnalyticsLifecycleToolkit:APracticalGuideforanEffectiveAnalyticsCapability.Hoboken, NJ: John Wiley & Sons, 2018, 448 pp.

7. <!-- [if !supportLists]-->Williams,S.(2016).BusinessIntelligenceStrategyandBigDataAnalytics:AGeneralManagementPerspective. Netherlands: Elsevier Science.

• FurtherLibraryResources:

1. <!-- [if !supportLists]-->BusinessanalyticsforSalesandMarketingManagers:HowtoCompeteintheInformationAge.

2. <!-- [if !supportLists]-->BusinessStatistics.

3. <!-- [if !supportLists]-->Makingbigdataworkforyourbusiness:aguidetoeffectivebigdataanalytics.

4. <!-- [if !supportLists]-->Managerialdecisionmodeling:businessanalyticswithspreadsheets.

5. <!-- [if !supportLists]-->Masteringdigitalbusiness:Disruptivetechnologiesareenablingthenextwaveofdigitaltransformation.

6. <!-- [if !supportLists]-->Masteringmarketanalytics:businessmetrics-practiceandapplication.

7. <!-- [if !supportLists]-->Practicalbusinessintelligence:learntogetthemostoutofyourbusinessdata.

8. <!-- [if !supportLists]-->Simulatingbusinessprocessesfordescriptive,predictive,andprescriptiveanalytics.

9. <!-- [if !supportLists]-->Strategicanalytics:advancingstrategyexecutionandorganizationaleffectiveness.

10. <!-- [if !supportLists]-->Tableau10businessintelligencecookbook.