1. The document discusses research on student learning characteristics and how they relate to choices students make in blended learning environments that combine online and face-to-face learning. 2. Data from over 800 students in business and economics programs is analyzed to identify clusters of students based on their use of online tutorials and participation in problem-based learning discussions. 3. Clusters are compared in terms of learning profiles and motivations, finding that students' digital learning behaviors do not always match the "ideal" for problem-based education and that different types of scaffolding may be needed.

1. Studentkenmerken en ICT-ondersteund leren: leerstijlen, doeloriëntaties en academische motivaties Dirk Tempelaar

2. Keuzeprocessen in ‘blended leren’: de student aan zet Veel internationaal onderzoek naar het ‘scaffolden van e-leren’: soms zijn digitale leertools dermate complex, dat het leren erin (voor sommige studenten) ondersteund moet worden door persoonlijke tutors. Onderzoeksvraag: voor wie? Maar het omgekeerde kan ook gelden: face-to-face leerprocessen zijn complex (student-gericht leren), digitaal leren kan daar een ondersteuning voor zijn. Meest brede vraag: als de student kan kiezen in vormen van leren, zoals digitaal vsface-to-face, welke studenten maken welke keuzes?

3. Maastricht’s blended learning Problem-based learning (adapted from McMaster University): collaborative learning based on social constructivist principles (with support of lecture cycles) Adaptive tutorial ALEKS: individual learning, with e-learning environment based on Knowledge Space theory (AI) This blended learning environment is our ‘statistical buffet’ for the students. Prime characteristic is that students continually choose from the buffet: it is not a one-time allocation based on student characteristics at the start of the course, but a repeated choice over a 8 weeks course period. Data for this study are 6 relative large (800/1000) cohorts of freshmen business / economics.

4. Process of PBL small group discussion problem * description of phenomena * prepared by a team of teachers * directs learning activities * what do we already know about the problem? * what do we still need to know about the problem? * using a specific problem solving technique (7-jump) self study exchange of information *learning resources *integration of knowledge from different disciplines * did we acquire a better under- standing of the processes involved in the problem?

5. How PBL? Seven-Jump Step 1: Read: clarify terms and concepts Step 2: Problem definition Step 3: Brainstorm Step 4: Systematic inventory Step 5: Formulate learning goals Step 6: Self-study Step 7: Report and synthesize

6. Roles * Tutor: monitors the process and content * Discussion leader: leads the discussion/ process: summarises, activates, asks questions * Secretary: “memory”of the group, takes minutes * Group members: participate and prepare!!!

7. Role of adaptive e-tutorial ALEKS in Statistics education ALEKS replaces all ‘practicals’ It adapts to the level of mastery of students, and thus takes into account prior statistics schooling, and in specific: lack of any prior schooling Participation is optional, and most strongly advised for students with no prior schooling Stats, and weak prior schooling Math Mastery is assessed in three Quizzes that allow students to achieve ‘bonus scores’ for their final exam. Strong students do not need such bonus, but for weaker students, it can be the difference between passing and failing.

8. UM solution: Adaptive e-tutorial: ALEKS

9. “Ideal” individual learning-path Based on outcomes of entry-assessment, a student could be evaluated at any point on the knowledge space of topic X. Student A can have a different learning path than Student D to reach point f Ideally, the learning materials and teachings methods should adapt to the knowledge/skills of each individual student.

10. ALEKS learning path Knowledge State can be described by All mastered items Outer Fringe (=Ready to learn ) + Inner Fringe (=Most recently learned)

11. Sample of an ALEKS assessment item

12. Partial sample of an ALEKS learning report

13. ALEKS: learning pie

14. ALEKS: Ready to learn & Log

15. ALEKS: Quiz report

16. ALEKS: Question

17. ALEKS: Explanation

18. ALEKS: Question

19. ALEKS: Explanation

20. Student learning characteristics Martin’s Student Motivation and Engagement Wheel

21. Martin’s Student Motivation and Engagement Wheel Boosters: thoughts and behaviors that enhance motivation & engagement Engagement: the behavior that reflects this energy and drive Motivation: students’ energy and drive to learn Mufflers (dempers): constrained or impeded motivation and engagement Guzzlers (verzwelgers): reducedmotivation and engagement

22. SMS correlations Mufflers Booster thoughts: SB self belief LF learning focus VS value school Booster behaviors: PS persistence PL planning SM study manag Mufflers: UC uncertcontr FA Failure avoid AN anxiety Guzzlers DS disengagem SS self sabotage

23. Self-regulated learning: Vermunt’s learning styles (patterns) model Learning styles composed of four components: Learning Orientations: students’ learning related attitudes and aims: Personally interested, Certificate directed, Self-test directed, Vocation directed, Ambivalent Learning Conceptions: beliefs and views on learning: Construction of knowledge, Intake of knowledge, Use of knowledge, Experience Stimulating Education, Cooperative Education Cognitive Processing Strategies: Critical processing, Relating & Structuring (together: Deep strategies), Analysing, Memorising & Rehearsing (together: Stepwise strategies), Concrete Processing Metacognitive regulation strategies: Self-Regulation of learning process, Self-regulation of learning content (together: Self-regulation), External Regulation of learning process, External regulation of learning content (together: Externalregulation), Lack of Regulation Cognitive Processing Strategies and Metacognitive regulation strategies are hypothesised to distinguish deep learners (deep strategies, self-regulation), stepwise learners (stepwise strategies, external regulation) and undirected learners

24. ILS Cognitive Processing Strategies - ‘Cognitieve verwerkingsstrategien’ Relateren & Kritisch verwerken Samendiepgaandleren (onderdeelbetekenisgerichteleerstijl) Memoriseren & Analyseren Samenstapsgewijsleren (onderdeelreproductiegerichteleerstijl) Concretiseren Onderdeeltoepassings-gerichteleerstijl

25. ILS Metacognitive Regulation Strategies - ‘Metacognitieve regulatie strategien’ Zelfsturing leerproces & Zelfsturing leerinhoud Samenzelfsturing (onderdeelbetekenisgerichteleerstijl) Ext. sturing leerproces & Ext. sturing leerinhoud Samenexternesturing (onderdeelreproductiegerichteleerstijl) Stuurloos Onderdeelongerichteleerstijl

26. ILS Learning orientations / leerorientaties Persoonlijk geïnteresseerd (betekenisgerichte leerstijl) Certificaat/diploma gericht( reproductie-gerichteleerstijl) Testgericht ( reproductie-gerichteleerstijl) Beroepsgericht ( toepassingsgerichteleerstijl) Ambivalent ( ongerichteleerstijl)

27. ILS Learning conceptions / leerconcepties Constructivistisch, opbouwen kennis (betekenisgerichte leerstijl) Opnemen van kennis( reproductie-gerichteleerstijl) Gebruik van kennis ( toepassingsgerichteleerstijl) Stimulerendonderwijs ( ongerichteleerstijl) Cooperatief/ samenwerkend ( ongerichteleerstijl)

28. Instruments:Dweck’s model of self-theories: Theories of Intelligence scales: Subscale: entity theory You have a certain amount of intelligence, and you can’t really do much to change it. Your intelligence is something about you that you can’t change very much. To be honest, you can’t really change how intelligent you are. You can learn new things, but you can’t really change your basic intelligence. Subscale: incremental theory No matter who you are, you can significantly change your intelligence level. You can always substantially change how intelligent you are. No matter how much intelligence you have, you can always change it quite a bit. You can change even your basic intelligence level considerably. Remark: In most empirical work, Dweck and co-authors do not include a separate entity and incremental subscales, but do regard one bipolar scale, called implicit theory, with the incremental position and the entity position as the opposite poles.

29. Dweck’sviews on the role of effort in learning Dweck & Blackwell hypothesize that implicit theories determine how students view effort. In the entity-theory framework, (the need for) effort signals low intelligence, thus effort is viewed as a negative thing. In the incremental-theory framework, effort is the cue to learning, to enlarging one’s intelligence, and thus viewed as a positive thing. Subscale: Effort as a negative thing, exerting effort means you have a low ability When I work hard at my schoolwork, it makes me feel like I’m not very smart. It doesn’t matter how hard you work—if you’re not smart, you won’t do well. If you’re not good at a subject, working hard won’t make you good at it. If a subject is hard for me, it means I probably won’t be able to do really well at it. If you’re not doing well at something, it’s better to try something easier. Subscale: Effort as a positive thing, exerting effort activates your ability When I work hard at my schoolwork, it makes me feel I am learning a lot. When something is hard, it just makes me want to work more on it, not less. If you don’t work hard and put in a lot of effort, you probably won’t do well. The harder you work at something, the better you will be at it. If an assignment is hard, it means I’ll probably learn a lot doing it.

30. Dweck: intelligentiezelftheorien en inspanningsopvattingen Zeerbeperktecorrelaties. Uitzondering: positieverolvoorinspanning

31. Dweck’s Goal choice: learning goal versus performance goal Dweck hypothesizes that (1) implicit theories determine achievement goals, and (2) this relationship relates to relative, not absolute, measures of learning (mastery) and performance goals. So the suggested scale is again bipolar, pitting learning goals against performance goals. However, the scale does not perform well (included in model as dependent, but not as independent construct). Alternative tool in Dweck’s work: PALS (revised version), and repeated here: Mastery goal, Performance Approach goal, Performance Avoidance goal Grant & Dweck (2003) instrument: 4 Performance goals, 2 Learning goals Outcome performance goals: goal of wanting to do well on a particular task Ability performance goals: goal of seeking to validate one’s ability Both Outcome and Ability goals allow a Normative version (wanting to perform better than others) and a Non-normative version (absolute standard). Learning goals with & without explicit challenge-mastery component. Total spectrum: Outcome goal, Ability goal, Normative Outcome goal, Normative Ability goal, Learning goal, Challenge-Mastery goal

32. PALS: doelorientaties Mastery: omteleren Performance Approach: prestatie-motivatie Performance Avoidance: Vermijdings-motivatie

33. Dweck’s outcome performance, ability performance & learning goals Outcome goal Ability goal Normative Outcome goal Normative Ability goal Learning goal Challenge-Mastery goal Normatief: vergelijkenderwijs Niet-normatief: absoluut

34. Metacognition:AILI: Awareness of Independent Learning Inventory Developed by researchers of University of Amsterdam: Elshout-Mohr, Meijer, van Daalen-Kapteijns, and Free University of Brussel: Meeus Based on Flavells three component model: knowledge, skills, attitudes. Balanced design with regard to positively and negatively phrased items. K: Metacognitive Knowledge K1: in the person category K2: about strategies K3: about study tasks R: Metacognitive Skill: R1: orientation on one's own functioning in a learning episode R2: monitoring one's execution of a learning episode R3: evaluation of one's own functioning in a learning episode O: Metacognitive Attitude (sensitivity to feedback): O1: sensitivity to metacognitive experiences (internal feedback during learning) O2: sensitivity to external feedback on one's cognitive functioning O3: curiosity with respect to one's own cognitive functioning and development

35. Metacognitievevaardigheden K: kennis van R: vaardig in O: attitude, sensitiviteit

36. Expectancy-value based model for Achievement Motivations (subject Attitudes) The SATS model describes the relationships between achievement motivations toward the subject statistics. It originates from the Expectancy-Value model Eccles, Wigfield and co-authors, and is adapted to the statistics domain. Expectancy for success: Competence belief, belief in one’s own ability to perform a task Perception of task demand, the perceived (lack of) difficulty of the task demand Subjective task Value; one component, containing: Attainment values: importance of doing well on a task, Utility value: usefulness; Costs: spent efforts Subjective task Affect: Intrinsic value: enjoyment gained from doing the task Interest Effort (planned in ex ante, perceived in ex post version)

37. VakattitudesVerwachting*Waarde model (Exp * Value) Affectie: waarde Cognitievecompetentie: verwachting Value: waarde, extrinsiek Difficulty: verwachting Interest: waarde, intrinsiek Effort: inzet

38. Cluster analytic study Two-step cluster procedure on AleksHours and BBclicks Cluster 1: top e-ALEKS users, average BB Cluster 2: average e-ALEKS & BB Cluster 3: low e-ALEKS users, average BB Cluster 4: average e-ALEKS & top BB Cluster 5: average e-ALEKS & low BB Cluster 6: independent learners/drop-outs

39. Clusters compared on learning profiles Cluster 1: high on Stepwise, average on Deep, high on External. Clusters 3 & 6: low on all.

40. Clusters compared on learning profiles Cluster 6 is consistent: average on Affect, high on (no)Difficulty, low on Effort. Mirrored in Cluster 1: low in Affect, low in (no)Difficulty, high in Effort.

41. Context afhankelijkheid Conclusie 1: onze ‘digitale student’ vertoont kenmerken die deels tegengesteld zijn aan die van de ‘ideale pgo-student’ Conclusie 2: behoefte aan scaffolding kan dus verschillende richtingen opgaan: niet enkel de tutor die een complex leertool ondersteunt, maar ook de leertool die een complexe tutorgroep aanvult Conclusie 3: Blended leren voorziet op flexibele wijze aan persoonlijke ondersteuningbehoefte.