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What matters ?
1. What matters(?) B.L. William Wong Professor of Human-Computer Interaction Head, Interaction Design Center School of Engineering and Information Sciences Annual Learning and Teaching Conference 29 June 2010 ENGAGING THE DIGITAL GENERATION IN ACADEMIC LITERACY
2. Scope Digital Generation As Educators ⊠What matters(?) Academic literacy Engaging HCI Research Lessons from HCI Research for engaging the digital generation in academic literacy The 7 Habits 2
3. Academic Literacy: What is it? To engage in the on-going intellectual conversations Competencies in thinking, reading, writing, speaking Awareness of logical, emotional and personal appeals used in argument Understanding of audience, tone, language usage, rhetorical strategies Skills that enable one to define, summarize, detail, trace, explain, evaluate, compare and contrast, analyze and synthesize, dissect and (re)combine ideas, make connections to related topics, anticipate Critical thinking skills to enable complex analytical work Society has changed Nomadic â agricultural â industrial â knowledge Abstract problems Interpret, judge, and assemble evidence about value, significance or relevance Tolerate ambiguity Distinguish between results of conjecture vs evidence-based Intersegmental Committee of the Academic Senates (2002). Academic Literacy: A statement of competencies expected of students entering Californiaâs public colleges and universities 3
4. Academic Literacy: Why? Why does this matter? To foster success in higher education Success is motivating and addictive Affects retention and completions To be effective contributors and participants in advancing our communities and society Discernment Advancement Better citizens, better consumers 4
5. The Digital Generation The Generations Gen X => 1960 â 1970s Baby Boomers Gen Y => 1970s â 2000 Gen Z => early/mid-1990s â 2012 The Digital Generation, the Google Generation Those born and immersed into a world of technology, communications, constant connectivity, the WWW, instant messaging, text messaging, YouTube, MP3 players, mobile phones Our concern: Educating this generation How they learn, communicate and socialize differs significantly from previous generations They are now coming through universities To get the best out of them, we need to re-think how we teach 5
6. Google Generation: Typical Stereotype Web savvy young people whose first port of call for information is Google âOn the screen was some history/ physics/English document, but also his Facebook and iTunes pages. In his ears were the iPod plugs, playing back a podcast. And sometimes, just to fracture his concentration even further, he might have had a half-played video running on YouTube as well.â (Catherine OâBrien (2008). How the Google generation thinks differently, The Times, 9 July 2008, http://women.timesonline.co.uk/tol/life_and_style/women/families/article4295414.ece) 6
7. The Google Generation 89% of college students use search engines to begin an information search (while only 2 per cent start from a library web site) 93% are satisfied or very satisfied with their overall experience of using a search engine (compared with 84 per cent for a librarian-assisted search) search engines fit college studentsâ life styles better than physical or online libraries and that fit is `almost perfectâ college students still use the library, but they are using it less (and reading less) since they first began using internet research tools `booksâ are still the primary library brand association for this group, despite massive investment in digital resources, of which students are largely unfamiliar College Studentsâ Perceptions of the Libraries and Information Resources: A Report to the OCLC Membership. Dublin, OH: OCLC, 2006, in Information Behaviour of the Researcher of the Future: A CIBER Briefing Paper, Jan 2008, UCL 7
8. The Claims: How true is all this? Generally true: They are more competent with technology They have very high expectations of ICT They prefer interactive systems and are turning away from being passive consumers of information They prefer visual information over text (but text is still important) Open: They have shifted decisively to digital forms of communication: texting rather than talking They multi-task in all areas of their lives They are used to being entertained and now expect this of their formal learning experience at university They think everything is on the web (and its all free) They do not respect intellectual property They are format agnostic No: They have zero tolerance for delay and their information needs must be fulfilled immediately They find their peers more credible as information sources than authority figures They need to be feel constantly connected to the web They are the âcut-and-pasteâ generation They pick up computer skills by trial and error They prefer quick information in the form of easily digested chunks rather than full text They are expert searchers Information Behaviour of the Researcher of the Future: A CIBER Briefing Paper, Jan 2008, UCL 8
9. What is the extent of this? 27% of UK teenagers could really be described as having the kind of deep interest and facility in IT as the term âGoogle Generationâ suggests 57% use relatively low level of technology to support their basic communication or entertainment needs 20% who actively dislike and avoid using technology whenever possible Synovate (2007). Leisure Time: Clean living youth shun new technology. www.synovate.com/current/news/article/2007/02 9
10. Digital Natives, Digital Immigrants âOur students have changed radically. Todayâs students are no longer the people our educational system was designed to teach.â (Prensky, 2001) Digital natives â born into the world of technology and the internet Like receiving information quickly from multiple media sources. Like parallel processing and multi-tasking. Like processing pictures, sounds and video before text. Like random access to hyperlinked multimedia information. Like to network with others. Like to learn âjust in timeâ. Digital immigrants â those, not born, but have adopted technology Like slow and controlled release of information from limited sources. Like singular processing and single or limited tasking. Like processing text before pictures, sounds and video. Like to receive information linearly, logically and sequentially. Like to work independently. Like to learn âjust in caseâ. However, not everyone born in this period are ânativesâ, although they can be connected to it 10 Prensky, M. (2001). Digital natives, digital immigrants. On the Horizon, 9(5).
11. How do they search for information? Horizontal information seeking 60% of e-journal users view no more than 3 pages and the majority (65%) never return Navigation They spend as much time finding their bearings as they spend viewing what they found Viewers, rather than readers Typically (âpowerâ) browse for 4-8 minutes Squirreling behaviour Download and store Diverse information seekers Geography, gender, type of university, status ⊠all very different Checking information seekers Assess authority and trust by cross-checking Information Behaviour of the Researcher of the Future: A CIBER Briefing Paper, Jan 2008, UCL 11
12. The UBiRD study In total: 34 participants (16 female, 18 male) A Russell Group University: 12 (5 UG, 3 PG & 4 Researchers) A 1994 Group University: 10 (6 PG & 4 Researchers) Million+ University: 12 (5 UG, 4 PG & 3 Researchers) Two stage study: Stage 1: Focus Groups Stage 2: Observation & in-depth interviews ~ 2 hours 3 tasks of increasing difficulty and ambiguity to find information in library and non-library systems 68 hours of video and audio recordings Retrospective protocol analysis Wong, B. L. W, Stelmaszewska, H., Bhimani, N., Barn, S., & Barn, B. (2009). User Behaviour in Resource Discovery: Final Report. Available at: www.ubird.mdx.ac.uk, November 2009. JISC Grant Ref. Num. CSSERSA2 / SERV ENHANCE 12
13. User information search and retrieval 13 Search Start Points: Google, Wikipedia, YouTube etc = 19 / 34 Library resources = 4 / 34 Publishers resources = 12 / 34 PK/E Used: Friends and personal networks = 29 / 34 Wong, B. L. W, Stelmaszewska, H., Bhimani, N., Barn, S., & Barn, B. (2009). User Behaviour in Resource Discovery: Final Report. Available at: www.ubird.mdx.ac.uk, November 2009. JISC Grant Ref. Num. CSSERSA2 / SERV ENHANCE
14. e-Gov, e-Social Service Information: Citizensâ Advice Bureau Portal Information is hierarchically organized and silo-based Wong, B. L. W., Keith, S., & Springett, M. (2005). Fit for Purpose Evaluation: The case of a public information kiosk for the socially disadvantaged. In D. Benyon, J. Gulliksen & T. McEwan (Eds.), People and Computers XVIV, Proceedings of HCI 2005. (Vol. 1, pp. 149-165): Springer Verlag. 14
15. Users are looking for answers and relationships that span hierarchies and silos 15
16. Do low literacy users have problems accessing online information? 9 times longer to complete the task On average time spend on a task in seconds by high lit 84.81 and low lit 776.81 Visited 8 times more web pages On average for a task total number of pages visited by high lit 4.47 and low lit 39.56 Back-tracked 13 times more On average back tracked by clicking the back button by high lit .83 and low lit 13.19 4 times more likely to re-visit web pages On average revisited previously visited pages by high lit 12% and low lit 51% Spent 1/3 more time on a web page On average time spent on a web page in seconds by high lit 19.6 and low lit 21.85 13 times more likely to get lost On average lostness for the tasks by high lit 0.07 and low lit 0.91 They were generally less successful in finding information Kodagoda, N. & Wong, W. Effects of low & high literacy on user performance in information search and retrieval, in Proceedings of the 22nd British HCI Group Annual Conference on HCI 2008: People and Computers XXII: Culture, Creativity, Interaction - Volume 1. 2008, British Computer Society: Liverpool, United Kingdom. 16
17. 17 High Literate User Info Search Model Low Literate User Info Search Model Kodagoda, N., B.L.W. Wong, and N. Khan (in press). Information seeking behaviour model as a theoretical lens: High and low literate users behaviour process analysed as way of informing interface design. In Proceedings of ECCE 2010, the European Conference on Cognitive Ergonomics
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19. Supplied by many different sources, reside on possibly un-connected or loosely coupled data sets
20. Be of different formats such a numerical, video, photos, un-structured text
28. P. Pirolli, & Card, S. (1995). Information foraging in information access environments. Paper presented at the Human Factors in Computing Systems, CHI â95, Mosaic of Creativity, Denver, CO. 19 Information Foraging
29. Theories Theories Theories Theories Questions Questions Questions Questions Info. seeking strategies Info. seeking strategies Info. seeking strategies Info. seeking strategies Evidence Line of enquiry Evidence Evidence Evidence Knowledge reps Knowledge reps Knowledge reps Knowledge reps Investigators Investigators Investigators Investigators Lines of enquiry Lines of enquiry Lines of enquiry Lines of enquiry Recursive decomposition 20 Attfield, S. and Blandford, A., (in press) Making Sense of DigitalFootprints in Team-based Legal Investigations: The Acquisition of Focus.Human Computer Interaction Journal, Special Issue on Sensemaking
30. Workflow model 21 Attfield, S. and Blandford, A., (in press) Making Sense of DigitalFootprints in Team-based Legal Investigations: The Acquisition of Focus.Human Computer Interaction Journal, Special Issue on Sensemaking
31. 22 Qualitative Data Analysis: Emergent Themes Wong, B. L. W., & Blandford, A. (2002). Analysing ambulance dispatcher decision making: Trialing Emergent Themes Analysis. In F. Vetere, L. Johnston & R. Kushinsky (Eds.), Human Factors 2002, the Joint Conference of the Computer Human Interaction Special Interest Group and The Ergonomics Society of Australia, HF2002 (pp. CD-ROM publication). Melbourne.
32. Academic Literacy: Similarities across different domains Academic literacy shares many similarities with sense-making Competencies in thinking, reading, writing, speaking Awareness of logical, emotional and personal appeals used in argument Understanding of audience, tone, language usage, rhetorical strategies Skills that enable one to define, summarize, detail, trace, explain, evaluate, compare and contrast, analyze and synthesize, dissect and (re)combine ideas, make connections to related topics, anticipate Interpret, judge, and assemble evidence about value, significance or relevance Tolerate ambiguity Distinguish between results of conjecture vs evidence Frame of reference Knowledge of the subject or domain Theories and concepts Methods in the subject 23
33. Engaging the Digital Generation: Learn, communicate, and socialize Moving from Twitterâs 142 char to 1500 word documents that require integrative and sustained thinking, reflection and intellectual dialog Success in engaging the Digital Generation The Digital Generation Project http://www.edutopia.org/digital-generation Digi-Teen Project http://digiteen.ning.com/ Flat Classroom Project http://www.flatclassroomproject.org/ 24
34. âClassroom21â Project A pilot study to identify factors that influence how children learn with and through Information and Communications Technology University of Otago, NZ, in 2000 Standard 4 children (10-11 year olds) Prepare a core group of primary school teachers to develop multimedia and internet-based project such as a website that has QuickTime Virtual Reality environment and multimedia. Bradford Primary School, Kaikorai Primary School, MacAndrew Bay Primary School, St Clair's Normal School The children learnt the tools and methods QTVR Authoring Toolkit, KidPix, HyperStudio, Clarisworks,DreamWeaver, HomePage digital photography, art, sound, movie editing, storyboarding, webpage development Created a QuickTime Virtual Reality record of a site they visited and then to have that visit posted on the internet. e.g. Portobello Marine Laboratory, the Royal Albatross Colony, Larnarchâs Castle Children researched and reported on aspects of the visit Biology, marine life, the Royal Albatross, history Research skills: reading, writing, assembling Hot links created from the VR environments to relevant aspects of their research 25 Peterson, K. A, and Wong, W. B. L, (2000), Interactive Children: The Use of Virtual Reality and Web Technologies, Ozchi2000, C. Paris, N. Ozkan, S. Howard and S. Lu, Sydney, CSIRO Mathematical and Information Sciences, 12-14.
41. What matters(?) in these projects ⊠or at least, appear to matter: Empowerment Create-ability Collaboration 32
42. Empowerment: CRISIS FP7-SEC-2009-1 Grant Agreement No. FP7-242474 CRitical Incident management training System using an Interactive Simulation environment â⊠the attention span of a gnatâ? From computer games and training simulation CRISIS: What matters(?) System performance Good frame-rate, for several/many simultaneous players Realism Rendering, movement and physics visualisation - realism of objects and characters, including their rendering, as well as their movement in the scene Interaction â compatibility of I/O devices with the type of game or training Believable (socio-behavioral) scenarios Require situation assessment, and (team) decision making Require relevant expertise and competency Realistic decision making Collaboration and problem solving Storyline control Control over responses and what is to be done
43. Team work in crisis management: Similarities between the real-world, and online gaming environments Jane Barnett
49. Empowerment Control Control over how they act, respond and learn âClassroom21â Their teachers guided the learning Our researcher taught the technical skills The children controlled the design and development researching and developing the projects Deep vs shallow learning 36
50. Create-ability 3D-in-2D Displays for Air Traffic Control EUROCONTROL CARE INO III Innovation Research Programme, EEC Contract No. C06/12399BE 37
58. 45 Wong, B. L. W., Rozzi, S., Gaukrodger, S., Boccalatte, A., Paola, A., Fields, B., et al. (2008). Human-Centred Innovation: Developing 3D-in-2D Displays for ATC. In D. Vu N., A. Zellweger, D. George & J.-M. Garot (Eds.), Proceedings of ICRAT 2008, the Third International Conference on Research n Air Transportation (pp. Accepted for publication).
59. Create-ability Competence Knowledge and skills that enable them to carry out real tasks 3D/2D Sound understanding of the air traffic task, goals and constraints 3D/2D Understanding how technology affects how we do things, and how that changes the demands that places for new technology Courage and confidence Courage to apply, and ability to learn from their mistakes 3D/2D Novelty requires breaking the norm Creative and initiative Familiar with problem solving, lateral thinkers Initiates and tinkers (because it is seldom that we get it right the first time) 3D/2D Requires knowledge of state of the art, theories and concepts, operational concepts, and not just a wacky idea Critical thinking Slice and dice, analyze and dissect, distinguish between âshades of greyâ 3D/2D The 3Câs Framework â Containers / Controls / Content 46
62. Collaborate Co-discovery Collaborate and working in teams to discover or accomplish together Librarians and Users (researchers and students) to understand the problem in order to innovate Developers to flesh out the concept Communicate Able to articulate their ideas and to coordinate and implement them Particularly difficult as the novel concepts were very difficult to explain, and to overcome prior thinking 49
63. So, What matters(?): The 7 Habits Competence Knowledge and skills that enable them to carry out real tasks Control Control over how they act, respond and learn Courage and confidence Courage to apply, and ability to learn from their mistakes Co-discovery Collaborate and working in teams to discover or accomplish together Communicate Able to articulate their ideas and to coordinate and implement them Creative and initiative Familiar with problem solving, lateral thinkers Initiates and tinkers (because it is seldom that we get it right the first time) Requires knowledge of state of the art, theories and concepts, and not just a wacky idea Critical thinking Slice and dice, analyze and dissect, distinguish between âshades of greyâ 50
64. In Conclusion ⊠Digital Generation As Educators ⊠What matters(?) Academic literacy Engaging 51 What do we focus on? Technology Most visible, most tangible, most seductive
65. In Conclusion ⊠Digital Generation What matters(?) Academic literacy Engaging 52 Empowerment, Create-ability, Collaboration
66. In Conclusion ⊠Digital Generation What matters(?) Academic literacy Engaging 53 Empowerment, Create-ability, Collaboration The 7 Habits Competence; Control; Courage and confidence; Co-discovery; Communicate; Create and initiate; Critical thinking
'What matters (?)': As university educators, what should we be concerned about as we train, teach and educate, our students in an environment where technology is playing an increasingly larger part in the process? What can we learn from the so-called 'Google Generation' (do they exist?) about the use of technology to create learning environments that support the strategies that our students are likely or supposed to adopt? Does technology get in the way and hinder learning? does it really 'enrich' the learning experience? While technology is great at automation and standardisation, and hence the economic delivery of 'bundles' of knowledge, how can we use it as well to inculcate ingenuity, industry, and innovation? in the hope that our students will go on invent futures that make for a better society? In this talk, I will reflect on these questions as I review some of the projects we have been involved with to see what we can learn from them about 'What matters (?)' in educating our students for the future
Participants were recruited randomly; equally representingmale & female population (almost equally)The study was carried out in two stages: In stage 1: focus groups (2 groups - in total 9 participants) to identify vocabulary that users understand and use in the context of resource discovery systems, the vocabulary used during information search and query formulation and identify which electronic resources are used by the different user groups. From this information we developed three task scenarios of varying levels of difficulty and ambiguity that were used in the observation sessions. Electronic resources refer to In stage 2: part A: observational study was combined with a âthink aloudâ method that lasted about 1 h and in Part B we combined an in-depth interview with a cue recall technique. We adapted the Critical Decision Method and combined it with Cued Recall. CDM is a structured retrospective interview method that is used for learning about usersâ expertise and strategies invoked during a specific incident. ETA â technique that uses a concept distillation process to rapidly and systematically identify broad themes that are similar ideas, and concepts reported across interviews and observations. The data can be then identified, indexed and collated. The themes were collated and analysed across the different study groups across all three studied institutions.
During the observation studies we identified a set of steps that participants took while searching for information. Just in short here and Iâll explain each step in detail next.(i) Users starts with âInitiateâ, which is a process of staring the search activity. They define the subject, make sure that they understand the concepts, and define the keywords. Also they will decide on the selection of resources to use such as internal, external or personal/social network.(ii) Next is âSearchâ. It appeared that many of the users in the UBiRD study followed Spencerâs (2006) modes people experience when seeking for information. These modes of information search are: âknown-item searchâ (users know the accurate keywords), exploratory search (users might not know where to start to look, but they will recognise when they found the right answer), (iii) âListâunknown search (users donât know what they need to know, they may not have the right vocabulary but will recognise when they have found the right information, (iv) âevaluateâ(v) re-fine and reformulate - (users look for information that they found before, history search, something that they found before on the topic). These functions can supported by a variety of tools such as a single keywords, advanced multi-word and Boolean search, link and others . Iâll talk about them in detail later. (iv) Next stage if Select & reviewâ where users evaluate their list of results then based on that they can either change resources, (vii) âChange resourcesâ (viii) Store. We have added one additional mode âstorageâ to Spencerâs modes where users kept their relevant information. Refine or re-formulate the query, if they found something interesting they may âView Detailsâ (where they evaluate individual documents) or they may âAbandonâ the search for various reasons, which Iâll discuss later. (iv)Abandon
Lostness or the participants disorientation from the task (Smith, 1996) was calculated using the following equation: Lostness = â (Upages)/ (Pvisited -1)2 + (Opath / Upages -1)2 Lostness ranged from 0 to 2. Â Lostness is a ratio of total number of pages visited, optimal path and unique pages visited, if these values were similar the user was not lost as there is no diversion from the optimal path. Â If lostness equals 2 the participant was believed to be diverted from the optimal path or lost.
Data CharacteristicsVery large amounts of data, about many different and some possibly related, but much un-related topics, and within each topic area may have fragmentary information relating to several threads Supplied by many different sources, reside on possibly un-connected or loosely coupled data sets Be of different formats such a numerical, video, photos, un-structured text Varying quality, reliability, ambiguous, similar yet different Be incomplete with missing data, and out of sequenceEntities with unknown and unexpected relationshipsLacks contextStructuring Analytical ProblemsDecomposeIdentifying the components of the problem or situationUnderstanding their structure How the parts relate to each otherOften times the parts are not clearly related (ambiguity, uncertainty, missing ..)What assumptions needed? Are they valid?How does the evidence come to give a conclusion?ExternalizeBasic tools include: tables, lists, diagrams ⊠Methods for manipulating the data and their relationships in order to see and test alternative views and conclusionsRe-arranging (substituting, changing sequences); deleting, combining, modifying (what if �), re-conceptualizing, assigning more weight or significanceGenerating Alternative Possibilities Analysis of Competing Hypothesis
state of the art in terms of realism and interactivity(b) state of the art in terms of how the games are controlled at the user interface level, as well as at the substantive 'story' level  visualisation - realism of objects and characters, including their rendering, as well as their movement in the sceneinteraction - the physical i/o devices such as mouse, keyboard, PS3 controller, etc to control actions (complex and simple), and their compatibility with the type of game or training simulation eg AA3 vsTruSim(c) storyline control -  how situational information is presented to enable assessment, and determining and selecting what can be done (e.g. the long list in 'Preview Simulation' for training the paramedics is ridiculously long!)(d) multi-player coordination - what are the techniques used (for visualisation of the coordination, interaction (devices and interfaces) with the game so that affordances are clear, and how the storyline is controlled), so that players can see and coordinate their actions and maintain situation as well as team awareness?(e) voice communications (as in 'Ambush') is nicely used, and what / how do we do this?Training focusSituation assessment, and (team) decision makingExpertise, considerations, emotive stateRealismRendering, movement and physicsSocio-behavioral, and Believable scenariosEngagementCollaborative, project-based, authenticSystem performanceGood frame-rateNumber of simultaneous playersMoving away from procedural training into problem assessment, hypothesis formulation and action design and executionDecision makers who learn by applying their knowledge in realistic and interactive scenariosInteractivity provides immediate feedback on decisions and actions: to both right and wrong decisionsLearning to recognise and understand how knowledge is structured in the (simulated) worldTeam work and collaborationIndividual, in a team of avatars, in teams of people