Will now present some examples in the context of my work– will talk about technology
----- Meeting Notes (9/5/12 17:17) -----STELLAR was an attempt to support problem-based learning in teacher education through the uses of technology.
- analyze only steps 3 to 6 of the activity for each group, the line counts begin at different numbers for each group because Group 2 engaged more with the STELLAR tools in the earlier phases of the activity than did Group 1.The vertical axis shows the categories of tool hits, discourse codes, and speakers. The horizontal axis shows the number of tool-related events, either a log entry or a discourse turn. The bottom seven categories represent tool hits by any member of the group. The top six or seven categories represent the speakers.Group 1- weaker group, in Group 1, the facilitators were involved early and fairly frequently, and asked most of the explanatory and metacognitive questions. Ann and Fauna seemed to dominate the discourse though other students contributed. Task talk continued throughout duration of activity as they struggled to figure out what they were doingAnother aspect of how the CORDTRA diagrams help us distinguish the collaborative activity between two groups is by showing the overall relation between the discourse and the tool use. In Group 1, the students initially viewed the video and the Knowledge Web but after about line 650, none of the group members used these two resources until the very end of the collaborative phase at line 1000. The content of their online postings were intermixed conceptual, social, task and tool-related talk throughout their work on the problem. There was some discussion of tools as a problem midway through the discussion. ----- Meeting Notes (9/5/12 18:03) -----To better understand the variability, we created visual representation in which we examined the relation between discourse features and log data from using the various tools.CORDTRA-- builds on work of Rose Luckin-- Chronologically ordered representation of discourse and tool related activity all on a single timeline.
Group 2In Group 2, the facilitators joined in much later and made infrequent contributions in the form of questions. This is because in this group the students themselves asked a number of questions throughout the duration of the problem. The group participated fairly evenly except for Matt who chimed in late in the group’s work. His contribution built on one of the other student’s ideas and was grounded in personal experience. His later contributions offered an important new idea for an activity that was grounded in psychological theory. What is interesting in Group 2 is that they went back to the video and the Knowledge Web at intervals throughout the discussion (e.g., around lines 850-925, 1050-1100, 1275). It appears that group members did this following several explanation questions as Figure 7 demonstrates (for example at about line 1050). This suggests that Group 2 was using the resources of the video and the Knowledge Web in a purposeful manner. That is, they seemed to be using the STELLAR resources to answer the questions at hand. They were bringing together the problems of practice and conceptual ideas repeatedly. We hypothesize that it is the repeated meshing of conceptual ideas from the Knowledge Web with the perceptual ideas from the video, which is a precondition for transfer (see Derry, 2006). Our current analysis, however, did not test to see whether transfer in fact occurs.The CORDTRA demonstrates several other distinctions between the two groups with regards to timing. Group 2 engaged in group monitoring throughout the activity whereas Group 1 did not engage in this kind of monitoring until relatively late in the activity. This was generally a request for feedback from the rest of the group. Inspection of the data shows that it was the facilitator doing most of the group monitoring in Group 1 whereas in Group 2, it was the students who were the ones monitoring themselves. The facilitators adapted their support to the needs of the group and thus differentially engaged with each group as needed. ----- Meeting Notes (9/5/12 18:03) -----There are other distinctions I could mention, but from a methodological perspective, this allowed us to see how the different groups engaged in their problem solving task.
Participants viewed a brief video in which high school students learned about electricity, electrical circuits, and how a light bulb works. Before viewing the video, they received a brief written explanation describing how the video clip illustrated a problem the teacher had: that even top students were maintaining their pre-course misconceptions about electricity after instruction. The video explained how the teacher had spent a month covering advanced topics in electricity and provided hands-on experience designed to reinforce those concepts and illustrate how electricity enabled a light bulb to work. Video also showed an interview with a good student before and after instruction and demonstrated that she maintained the same misconceptions following instruction.They had thirty minutes to answer the following four questions: (1) How do you know that the student failed to learn? (2) Why did the student fail to learn? (3) What recommendations would you make to the teacher to help him improve his teaching? and (4) What else do you need to know to better understand the teaching-learning situation? What additional questions would you ask?
Group A- difficultydemonstrated by the need for the teaching assistant to frequently intervene and facilitate this group’s workGroup B- Both groups engaged with the concept of transfer and they showed this in how they used the technology
All students discussed in P1, number decreased in subsequent problems. All the students in this group used transfer in their independent proposals but did not use it as an idea in commenting on other proposals, suggesting that the members of this group used the concept in parallel without real knowledge building Jenny quote 1: This excerpt shows that the student brought in ideas about transfer through direct quotes that define the concept. This is much like knowledge telling (Bereiter & Scardamalia, 1987), as Jenny shared relatively unprocessed information with her group. Although this group continued to use the concept in independent proposals, it later became encapsulated as part of the group’s language and no longer required detailed explanation.
illustrates a more fluid use of the concept of transfer without needing to provide all the definitions, suggesting that the group members had achieved a shared understanding. This use of conceptual ideas was seen to an even greater degree in Group B.
, similar to Group A, the group members began by incorporating direct quotes as they shared information, as this excerpt from Kathy shows. But unlike the other group– she more carefully mapped the definition to the evidence in the video.
Preserves video and metadata by converting to digital formatOffers a research and teaching portalProvides analytic tools, customized ontologies, and personal spaceSupports individual work and group collaboration
Different methods help deal with the complexity of theoretical perspectives
Same pre and post tests as in other enactments– but here our research questions focused on how people used the VMC resources
Posted Assignment This week's assignment for online work involves a video and two readings, with threaded discussion, that follows class work on problem solving for the Ankur's Challenge task. The following questions are intended to guide discussion in your small groups (and will also be posted in the introduction to group discussion threads).
ACROSS GROUPS, THE PERCENT OF POSTED DISCUSSIONS RELATING VIDEOS TO OWN AND OTHERS’ PROBLEM SOLVING WAS STATISTICALLY SIGNIFICANT.THE PERCENT OF POSTED DISCUSSIONS ABOUT ENJOYMENT ACROSS GROUPS WAS STATISTICALLY SIGNIFICANT.GROUPS A & D MADE LESS REFERENCE TO EARLY INTERVENTIONS AND TO PRACTICE .
TABLE 2 SHOWS THAT FOR GROUP C, THE PERCENTAGE OF SS WHO RELATED VIDEOS TO ASSIGNED READINGS WAS STATISTICALLY SIGNIFICANT,
Answered this with qualitative analysis
Purposes include:purpose (e.g., research, professional development)We also wanted, for classes, to better understand design features
Part of goal was to get sense of terrain.
Used this to look at high and lesser quality analytics to help future instructors better design tasks and evaluate analytics. Help us in discerning additional criteria that distinguished high and low quality
This was derived from researcher-supplied themes– will be interesting to apply to the raw data.
Talk a little bit about move
Embedded in problem- design aquarium ,video of eutrophication of pond,
Describe the screen – variables, controls, graph, outputs, fish… controls: sunlight, nutrient runoffDescribe the screen and the purpose of this simulation. At this point they have already identified inverse relationships between O2 and CO2. That when the O2 is down, more fish die. The teacher has just reminded the whole class that the goal of the activity is to model how the fish died in the pond—to reproduce the conditions in the pond that resulted in the fish dying. They have been modeling a system that keeps the fish alive or to die of old age. Why is the O2 decreasing?----- [NEXT SLIDE]
Move from SBF CMP– need to explain this.
Note that a great deal of this work is in progress.
Typically, we look at an aggregate pre to post test gain, but in complex domains, this is not sufficient- need to know how students learn– where they start, which aspects of systems are harder than others.Question 1 we are beginning to gain traction on– analysis is ongoing– question 2 is on the burner/Microgenetic analysis
Coded from Drawings taken over 4 time points in a year--
To support our analysis, we constructed a graph) that depicts the group means for each systems dimension in Classroom 1. Students appear to have steep growth towards higher levels of Biotic/Abiotic and macro/micro dimensions but relatively more steady growth towards higher levels of SBF and Coherence dimensions that converge by posttest. From the start, students represented structures in terms of their behaviors or functions and made connections between phenomena (Coherence). However, these structures were primarily macroscopic and biotic. Students made more complex connections between Biotic/Abiotic structures (AA1) and between Macro/Micro structures (AA2) before reaching higher levels of SBF or Coherence. Finally, the inclusion of extraneous structures peaked at AA1 and then declined until no drawings included extraneous structures by posttest.Of course, means mask some of the variability but we are seeing some consistency in B:A preceding M;M in general and that making both of these are important for a coherent understanding– represented by both the coherence measure and sBF score.
We designed the interview to assess students’ generalization of mechanistic reasoning and to make sense of new problems related to aquatic ecosystems. In the first problem, students were shown a paper copy of their group-generated EMT model depicting factors that may have led to fish dying suddenly in a local pond. The students were then asked to label the model in terms of CMP and explain their reasoning. In the model (see Figure 1), the entire problem reflected the phenomena, the rectangular boxes represented components that were linked together by explanations of their mechanistic behavior. In the second problem, students were told that there has been a sudden increase in geese population around a lake that has resulted in changes to the aquatic ecosystem. They were shown three versions of EMT models (the first consisting only of components, the second had only mechanisms but no components, and the third consisted of numerous components, mechanisms connecting them and phenomena). Students were first asked to rank each model on a scale of one to three, with three being the most complete explanation about what happened to the lake ecosystem as a result of the overpopulation of geese. Next, students labeled the model they had ranked the highest and were asked to explain the criteria for making their selection.
To trace generalization of mechanistic reasoning from an AOT lens, we compared each student’s labeled model in task 1 with that in task 2. We identified items they labeled as identical in terms of CMP in both tasks and also kept track of areas where they exhibited differences (i.e., identified phenomena in one task as the entire model and in the other had it labeled as a mechanism).
As we compared students’ labeling of models, it was evident that a majority of students generalized the concept of components and phenomena. We observed that students would either circle the entire model or focus on the primary problem under investigation when asked to label phenomena. Additionally, almost all the students were quick to tag components as factors that may have led to the problem
Social coordinationBehavioral engagement refers to the degree of the group’s on-task behavior.Task engagement refers to the focus of engagement on efficient planning and what steps to take next to accomplish the task. Can also refer to a focus on manipulating the technology tool (but the rating does not reflect whether concepts or content represented).
Conceptual engagement is considered a continuum that ranges from content connections that are focused on the key question or task problem or relating to the real world/experiences to simple knowledge telling. Note: The conceptual and consequential connections do not need to be accurate.To warrant a high rating, students need to go beyond referencing the larger question of why do fish die, for example, to making a connection with evidence or content. Also, a connection to a simulation or piece of evidence is still a medium rating, unless connected to the larger question.Medium: Group discusses and identifies content relationships between visible and invisible components.Low: simply reading the hypermedia; only interpreting simulation data without content relation (nutrients go up).We are seeing trends that the simulations foster high conceptual consquential engagement, task engagement, and behavioral engagement– more variability with EMT modeling tool.
Technology can play important role, but is synergistic with creating engaging contexts that create need for knowledge, bringing hard and soft scaffolds together– thinking about how to distribute scaffolding– also need to examine learner activity
technology to support complex learning
Cindy E. Hmelo-SilverRutgers University
Complex LearningProviding Scaffolds and Creating ContextsProblem-based Learning: STELLARCreating contexts with the VMCComplex Systems: Systems and Cycles
We live in a complex and dynamic worldNeed to go beyond learning isolated knowledgeand facts Useable knowledge Soft skills (Derry & Fischer, 2007)Preparation for lifelong learning, reasoning, andproblem solving (Fischer & Sugimoto, 2006) Useable knowledgeTransfer, from a range of perspectives
Such learning: Often situated in problem-based and inquiry learning environments (Hmelo-Silver, Duncan, & Chinn, 2007) Potential for excessive cognitive load (van Merriënboer, Kirschner, & Kester, 2003)Appropriate scaffolding and contexts to dealwith cognitive and social challenges
Provide support to allow learners to Competently do task Learn from taskBuilds on notion of ZPD (Vygotsky, 1978)Scaffolding complex tasks through Structuring ProblematizingThree primary kinds of scaffolding Communicating process Coaching Eliciting articulationHard and soft scaffolds (Saye & Brush, 2002)
Contextual support Video, Hypermedia in STELLAR (Teacher Education) VideoMosaic Collaborative Repository (VMC) Systems and Cycles simulationsCollaboration spaces STELLAR whiteboards, threaded discussionAccess to structured information STELLAR Knowledge Web VMC metadata Systems and Cycles hypermediaScaffolding through Interface and activity structures pbl online in STELLAR VMC analytic Systems and cycles curriculum materials
Processes Collaborative knowledge building Engagement Learning trajectoriesOutcomes Application Transfer Expert perspective (e.g., Barnett & Ceci, 2002) Preparation for future learning (e.g., Schwartz & Bransford, 1998; Schwartz & Martin, 2004) Actor-oriented transfer (Lobato, 2006)
With Sharon Derry, AnandiNagarajan, EllinaChernobilsky
Initial implementation (Hmelo-Silver, 2000) Paper cases One wandering facilitator for 6-7 groupsLimitations Cases were oversimplification One wandering facilitator for 6-7 groups Difficulty identifying fruitful learning issues because of limited and variable prior knowledge
Creating Context: Provide rich video cases of practice Concepts in contextScaffolds PBL online activity structure: extend skilled facilitation resources Knowledge Web: CFT Hypermedia support for generating learning issues
Pre-post across institutions using video analysistask Significant pre to post gains for both sites, with different implementationsQuasi-experimental design over 3 semesters Participants: 101 STELLAR PBL students in 18 groups 126 comparison students from Educational Psych subject pool Tracer concepts “Understanding” on video analysis Moderate to large effects over three years Between group variability striking
Group 1 Facilitator CHS Ann 50 Fran Cathy Fauna Luke 45 Other monitoring SDL Group monitoring Individual monitoring 40 Grounded beliefs Personal beliefs Elaborations 35 Explanations Transforming Elaborated telling Telling 30 Acknowledgement SummaryCodes Disagreements 25 Agreements Modiﬁcations New Ideas Metacognitive questions 20 Explanation questions Information questions Personal talk Concept talk 15 Tools as help Tools as a problem Task talk 10 View Other Proposals Research Library White Board Discussion Board 5 Notebook KW Video 0 300 400 500 600 700 800 900 1000 1100
Group 2 Facilitator CHS Matt Bob 50 Carla Caitlin Liz Helen 45 Other monitoring SDL Group monitoring 40 Individual monitoring Grounded beliefs Personal beliefs Elaborations 35 Explanations Transforming Elaborated telling Telling 30 Acknowledgement SummaryCodes Disagreement 25 Agreement Modifications New Ideas Metacognitive questions 20 Explanation questions Information questions Personal talk 15 Concept talk Tools as help Tools as a problem Task Talk 10 View Other Proposals Research Library White Board 5 Discussion Board Notebook KW Video 0 450 550 650 750 850 950 1050 1150 1250 1350 1450 Lines
Similar type of rubric developed to measure“transfer” (Hmelo-Silver et al, 2009) on 0-3scaleComponents of transfer rubric:1. requires understanding,2. involves activating appropriate prior knowledge and applying something learned in a new situation,3. involves abstraction and cognitive flexibility,4. can be near or far transfer, and5. can be preparation for future learning.
Pretest and Posttest Scores by Class Type Class N Pretest Posttest STELLAR 33 0.71 (0.31) 2.02 (0.69) Traditional 37 0.61 (0.36) 0.68 (0.34) F (1,67) = 114.323, p < .001, d=2.55
Large variability in groupsExamined STELLAR whiteboards for contrastingcases analyses Engagement with “Transfer”Group A 6 female students who had some difficulty Mean gain= 1.40, SD=0.89Group B 6 female students, rarely needed any assistance Mean gain= 1.33, SD= 0.61
Discussed transfer in 3 of 4 problems In Problem 1, Jenny proposed explanation for enduring understanding that child in video developed:“In the case of Brandon, he needed to have anunderstanding of how and why he was able to solvethe block problem in order to transfer his ideas ontothe pizza problem. "The first factor that influencessuccessful transfer is degree of mastery of the originalsubject" (How People Learn, 53). Brandon was able tocontinue to solve such a problem because of hiscomplete understanding of how he was able to arriveat the solution for the block problem.”
In problem 2, Rina used the concept of transfer in thinking about assessment as she offered this proposal:…The portfolio should have a final summary of the studentswork and questions regarding the students learning, so thatthe students can explain and evaluate their own thinking.(knowlege web [sic]) The students should be able to transfertheir prior knowledge of concepts such as force and motionin order to create their vehicle, while also allowing theactivity to expand on that knowledge. …another importantfacet of understanding is application (sic). Ms. Baker willknow whether the students acquired enduringunderstanding by how much they can apply this knowledgeto real world problems. One way of doing is to have Ms.Baker create another problem that will use the sameconcepts in a real world setting, and evaluating whether thestudents were able to apply the concepts they had learned.
All students mentioned transfer in P1; 2-4 students in subsequent problems Kathy wrote:…Second, Brandon was able to recognize a connectionbetween the pizza problem and the tower problem that hedid weeks earlier. Moreover, he made this connectionrelatively quickly and without much effort. He was able toshow us, by using his chart and the manipulatives (blocks),exactly how the pizza problem mapped into the towerproblem. His understanding of the pizza problem thereforefacilitated a new, and deeper, understanding of the blockproblem; this process is called transfer. Brandon’s seeminglyeffortless use of transfer provides evidence that heunderstood the problem, because “transfer and wideapplication of learning are most likely to occur whenlearners achieve an organized and coherent understandingof the material.” (How People Learn, p. 238-239)…
On later problems, fluid application of concept part of shared understandingMicki writes:…another way to look for enduring understanding would be the studentstransfer and application of principles of force and motion especially toreal world situations. This would show the students understandings ofinformation previously and transfer it to the problem at hand, which is areal world problem that allows students to work with hands-on material. Mimi followed this up by incorporating Micki’s comment and a previous proposal from another group member:To put these two ideas together, [t]he teacher could bring togetherindividual explanation and transfer as evidence of enduringunderstanding. An activity could be created at the end of each projectthat would ask the individual members of the group to use the principlesgained to explain a real world scenario. Likewise, an activity could bedesigned to facilitate transfer of the instructional objectives. For instance,one of the objectives was learning the scientific inquiry process. Theteacher could present a real world problem that would require thestudents to use the same scientific process to solve. (This would alsofacilitate transfer)
Technology: Scaffolds ContextComplex measures: Knowledge in use More and less productive collaborations
with Carolyn Maher, Marjory Palius,Grace Agnew, Robert Sigley, ChadMillswww.videomosaic.org
Preserves a major video data collection on studentreasoning From diverse schools settings To be available as open source From 40 doctoral dissertationsMakes available new tools for Teachers Educators ResearchersFrom longitudinal/cross sectional studies spanning25 yearsVideos following the same student cohort fromelementary school through high school and beyondOver 4500 hours of video
Importance of making sense of students’ conversations and how tools mediate learning (Hmelo-Silver, 2003) Being aware of the contextual resources (media, other Ss, prior experience) that Ss use influence collaborative knowledge construction (Arvaja et al., 2006) Attending to social interactions in collaborative knowledge construction (Palincsar, 1998)30
Graduate Online Designmathematics ed eCollege CMShybrid course Streaming video /Four online groups linked papers2+ week unit Minimal online In class problem instructor intervention solving Data Individual study of Postings from online videos and related threaded discussions readings Pre and post tests Group discussion (math, Ss reasoning) questions
To what extent do videos and readings promote online discussion within and across groups? How do learners relate practice to online discussion? To what extent do Ss relate videos to readings in their online discussions?32
All posts coded for comments related to Video (V) Readings (R) Additional sub categories of comments relating videos/readings to: Own problem solving (PV/PR) Others’ problem solving (OV/OR) Earlier interventions (EV/ER) Affect (AV/AR) Practice (TV/TR)33
Shows two groups of 10th graders (2 in one & 3 in other) working on the problem: How many different block towers can be built, four tall, selecting from three colors of blocks such that the towers have at least one block of each color? Approximately 8 minutes http://hdl.rutgers.edu/1782.1/rucore00000001201.Video.00006205534
(1) Describe Romina’s strategy for solving the Ankur’s Challenge problem.(2) In your opinion, is this solution a convincing one? Why or why not?(3) According to the Yackel & Hanna chapter, both von Glaserfeld and Thompson equate reasoning with learning (p. 227). From this perspective, in what ways do explaining and justifying contribute to learning mathematics?
Percent of Posted Discussions Related to Video Activity OverallSS Relate Videos N aand Readings to: A B C DOwn problem 27 100.0% 100.0% 100.0% 83.3% 95.7%solving (PV/PR)Others’ problem 13 100.0% 100.0% 100.0% 85.7% 92.3%solving (OV/OR)Earlier 10 66.6% 100.0% 100.0% 33.3% 70.0%interventions in theclass (EV/ER)Enjoyment 20 100.0% 83.3% 100.0% 80.0% 90.0%(AV/AR)Practice (TV/TR) 24 25.0% 71.4% 75.0% 12.5% 40.7%a N= Number of posts
Percent of Posted Discussions Relating Videos to Assigned Topic Readings Discussion Group A B C DSS relate videos to 16.7% 16.7% 45.5%* 7.1%assigned readings(RV)Number of posts 18 18 11 14
Across all groups: Studying videos generated reflections about own and classmates’ problem solving Studying videos of students’ reasoning was enjoyableBut still left us with question of ways in whichwhich Ss related resources to their practice
Create multimedia artifacts using the VMC repository Narrative with video for purpose Variety of uses by instructors, researchers Goal to classify and identify what differentiates high quality and low quality “analytics” Data sources: 27 VMCanalytics from several different classes and researchers Work very much in progressAgnew et al, 2010; Hmelo-Silver et al., in press
VMC Analytic by Hmelo-Silver (2011)VMC Analytic by Horwitz (2011)
Math LS Class Depth Depth Clarity CoherenceDesign-basedResearch 0.78 1.00 1.22 1.33Intro toMath Ed 1.96 1.80 2.36 2.20CriticalThinking 2.00 2.40 2.30 2.00Practicum 3.00 2.25 2.63 2.63No Class 1.17 1.67 3.00 3.00
Looking deeper with contrasting case analysisExample 1: Analytic illustrating how students can movefrom particular to general Concepts from both learning sciences and mathematics clearly articulated Indicative of designers understanding of students’ learning trajectoryExample 2: Analytic illustrates teacher questioning duringearly algebra exploration Students claims not supported by video segments selected Textual descriptions of events were vague Video not well chosen for intended purpose of relationship of teacher questioning and student engagement
VMCAnalytics coded foremergent themesExplored use of wordclouds as a learninganalytic Mathematics Education Word Cloud of coded Mathematics themes ideas Learning Sciences ideasAllow us to see dominantthemes within the two Word Cloud of coded Learning Sciences themesareas of interest
with Rebecca Jordan, Catherine Eberbach,Suparna Sinha, Lei Liu, Steven Gray, WesBrooks, Yawen Yu
Goals Learning about ecosystems Reasoning about evidence Modeling6 week curriculumCreating ContextsScaffolding complexlearningUnderstanding how andwhy along with what
Aquarium DesignEutrophication inlocal pondMarines problemscaused by oceanacidification
Provide context for: Help focus on function Discussions and behavior Science practices Make invisible visible Engage with complex and open for inspection systems phenomena
Use the following arrows to help you decide how the evidence relates to the differentexplanations: Solid Arrow Evidence supports the model Conceptual Wavy Arrow Evidence strongly supports the model Evidence contradicts representation X Crossed Arrow Dashed Arrow (disagrees with) the model Evidence neither supports nor contradicts the model SBF CMPLink each evidence box to each of the model boxes, using the arrows. On the nextpage, write your reasons for the three most interesting or important arrows. Worksheets EMT Teacher Model A Evidence 1 Model B Evidence 2 Model C
Reliable pre to post test gains on systems idea Connections across system levels SBF Macro-microIndividual and group variability
Learning trajectories (Eberbach, Hmelo-Silver etal., 2012)Engagement with content (Sinha et al., 2012)Participation in practices (Eberbach & Hmelo-Silver, 2010; in prep)Transfer Multiple perspectives (Yu, Hmelo-Silver et al., 2013; Sinha, in progress)
Developing ecosystems understanding ismultidimensional AbioticBiotic MacroMicro StructureFunction/BehaviorDimensions may develop differently (Wilson,2009)How are they influenced by particular aspects ofinstruction?Classroom microgenetic analysis (Chinn, 2006)
3 B:A M:M2 Extraneous SBF Coherence1 Pre AA1 AA2 Post
Often a goal of schooling– but hard to find inthe labDo students transfer ecosystems concepts fromone context to another? Aquatic RainforestFocus on tracer concepts that were targets ofinstruction Photosynthesis Cellular Respiration Decomposition
Example of presence of “plants use energy” andExample of “organic compoundspresence of are produced”“gas isexchanged”
AOT perspective focuses on how studentsperceive similarities (Lobato, 2006; Sinha etal., 2010)Pre and post interviews of 38 students from 2schoolsTask Label groups EMT model in terms of CMP Label EMT model of
Frequencies of students’ generalization of CMP Levels of CMP transferTotal n No C C&P C&M CMP Transfer transfer transfer transfer transfer38 3 (8%) 15 (39%) 7 (18%) 1 (3%) 12 (31%)
Work in progress (Sinha et al, in prep)Goal: Relating engagement to transfer Social coordination Behavioral Task ConceptualConsequentialCoding of video as students work on modelingand simulations 5 min intervals
Coding Conceptual-Consequential (CC)Engagement High (3) Medium (2) Low (1) Connects to other Focused on content Focus on low-level sources of knowledge connections and declarative knowledge; and experiences conceptual facts understanding, but do Reflects on larger not necessarily reflect or question or problem (e.g. go back the central why do fish die). question or relate to the real world. ‘0 ‘ Code was assigned when teacher was addressing the entire class.
• Creating need to know Context Scaffolds • Technology allows engagement Learner with complex phenomena activity • Video • Simulations • Distributed scaffolding helpComplex understanding manage complexity • BUT need to examine both participation and outcomes
National Science FoundationInstitute for Education SciencesQuestions? email@example.com