Study MACREDIEResearch The influence of gender on communication efficiency and effectiveness.Question Are males better at route tasks with a partner?Sample Size 56 participants (31 males and 25 females) – from a UK university (various departments) – random groupingExperiment • Wizard of Oz experiment (2 people interact; one of whom thinks they are talking to a system) – Masking gender & seated in separate rooms • Instructors were made to believe they were talking to a robot + they had no dialogue or script • User had to guide robot to 6 designated locations (in fictitious town) • Only instructors had view of the map and destinations • They were talking to a robot, so they could not assume that there was shared knowledge. • MM/MF/FM/FF – pairings • Custom system developed for real time text communication • System kept a log of dialogue & kept a log of the robot co-ordinates each time a message was sent (meaning that they can analyse the text description) • User controlled robot with arrow keys • Users were given verbal and written instructions and a demonstration • They were informed that the robot could learn routes – so they wont guess it’s a human • They can use forward, back, left and right, but not north, south…. (reducing confusion)
Study MACREDIELit review • Strengths • 15 references in quite a small ‘background’ / lit review section • Type of paper – IEEE - Conf - ACM • Weaknesses • A lot of references supported by Allen and DenisData • Study yielded 160 dialogues, 1460 instruction unitsAnalysis • Quantitative analysis of relevant data (time taken to complete task, number of words, turns and instructions in each dialogue) • Qualitative discourse analysis (number of miscommunication; granularity of instructions)Results from • Gender and role both have significant impactanalysis • Female instructors had to give less information when the follower was male • Male robots/followers had the leased execution errors and misunderstandings • Previous studies predict male superiority in both roles – mixed pairs actually exceeded or matched male performanceFuture • How it can be applied in a wider contextresearch • Identify drivers and non drivers to ensure better resultsResearch • Motorist thingflaws / gaps • Is spatial communication the same in other languages?
Study LOUVIERISResearch Military decision making for commanders to enable them to make rapid decisions by using CSF’s (criticalQuestion success factor – the area in which satisfactory results ensure competitiveness)Sample Size A few subject matter expertsExperiment • Used subject matter experts – to identify critical information requirements • Case based reasoning (analogical reasoning) • Bayesian belief networks (a mind map of factors – how each factor flows into the next – training impacts on quality, impacts on morale) • Simulation software – to see the effect of the case based reasoning (using Bayesian belief networks (how old related factors, map to new scenario)) – system spits out key information for decision makers • Like for like analysis between system and people on decision making.Lit review • Different methods of decision making – with and without systems (e.g. fire fighting – no time to make long decisions. Usually experience decision makers used RPD (recognition primed decision making) where pattern matching identifies a decision) • Strong references • Over reliance on his own referencesData Analysis • Analysed against traditional human based decisions • Collated responsesResults from • A solution which provided automated CSF identification and quantifications.analysis • This reduces decision makers workload through supported situational awareness (SA: The perception of the environment you are in with regards to time and/or space) • Contributes to CSF research; use of BBN research • Automated configuration of conditional probability tables (the factors of a decision and how they are related. Part of BBN) is produced.Future research • How can case based reasoning and BBN be applied in other domains?
Study YOUNGResearch Time to rethink healthcare and ICTQuestionSample Size 0Experiment Case study reviewsLit review Surrounded IS failures - 12 referencesData • Similarities and differences between healthcare and other sectorsAnalysisResults from • Enterprise systems cant be used for national healthcare initiativesanalysis • Person to person (collaborative) models are required • New model required, start from scratch • Getting the healthcare community to consider IS models, and looking @ failures before planning a new system.Future • Finding / developing a model which can be adopted by healthcare systemsresearchWeaknesses • No primary research • Old (late 80’s and early 90’s) case studies
Study ELLIMANResearch What are the gaps in the research area “ICT for governance and policyQuestion modelling”. What needs to be addressedSample Size Not ApplicableExperiment Not ApplicableLit review • As a background section – 4 references but only an initial report • Lists 64 project with grant funding of about 80M eurosDataAnalysisResults fromanalysis