WEBVTT 00:00:13.000 --> 00:00:15.000 » BRIAN COUCH: Welcome, 00:00:15.000 --> 00:00:20.000 everyone. 00:00:20.000 --> 00:00:24.000 » We have Dr. Joanne Lobato 00:00:24.000 --> 00:00:27.000 here. So before we get started, so just a reminder 00:00:27.000 --> 00:00:31.000 that this is the keynote speaker and then we will do 00:00:31.000 --> 00:00:36.000 the -- we will go into the other concurrent sessions 00:00:36.000 --> 00:00:41.000 after a short break after the end of this 00:00:41.000 --> 00:00:46.000 talk. If you have questions during the talk, add them to 00:00:46.000 --> 00:00:50.000 the chat and I will moderate the questions at the end of Dr 00:00:50.000 --> 00:00:54.000 . Lobato's talk. Videos have become integral to teaching 00:00:54.000 --> 00:00:57.000 across all of the disciplines. Our next speaker Dr. Joanne 00:00:57.000 --> 00:01:01.000 Lobato has researched how students learn while watching 00:01:01.000 --> 00:01:05.000 other students engage in dialogue to solve math 00:01:05.000 --> 00:01:07.000 problems. D r. Lobato is a professor in the department of 00:01:07.000 --> 00:01:12.000 mathematics and statistics at San Diego State University and 00:01:12.000 --> 00:01:16.000 a researcher at the center for research and mathematics. She 00:01:16.000 --> 00:01:20.000 is well known for developing autocar oriented transfer 00:01:20.000 --> 00:01:23.000 perspective n this perspective the researcher works for the 00:01:23.000 --> 00:01:26.000 ways in which students, also known as the actors connect 00:01:26.000 --> 00:01:29.000 transfer and learning situations rather than 00:01:29.000 --> 00:01:34.000 predetermining what counts as transfer from the expert's 00:01:34.000 --> 00:01:36.000 perspective. Actor oriented transfer helps detect 00:01:36.000 --> 00:01:39.000 generalizations of learning experiences and allows for 00:01:39.000 --> 00:01:46.000 prior experiences including the social context to affect 00:01:46.000 --> 00:01:50.000 transfer. Recent research focuses on how students 00:01:50.000 --> 00:01:54.000 learn vicariously while watching dialogues. Today's 00:01:54.000 --> 00:01:59.000 talk will be relatable for all since it draws on vicarious 00:01:59.000 --> 00:02:03.000 learning studies from a variety of disciplines. Her 00:02:03.000 --> 00:02:07.000 work is entitled dialogic online videos in STEM learning 00:02:07.000 --> 00:02:09.000 . Thank you for joining us Dr . Lobato. I'm going to turn 00:02:09.000 --> 00:02:10.000 it over to 00:02:10.000 --> 00:02:13.000 you. » JOANNE LOBATO, Ph.D.: Thank 00:02:13.000 --> 00:02:18.000 you, Joe. Of all of the areas of research in my career so 00:02:18.000 --> 00:02:23.000 far, this current project about new models of online 00:02:23.000 --> 00:02:27.000 videos is definitely been the most fun. So I'm going -- I 00:02:27.000 --> 00:02:35.000 have the honor to talk with you about it today. 00:02:35.000 --> 00:02:40.000 As Joe mentioned, the pandemic has forced us all to go to 00:02:40.000 --> 00:02:43.000 online instruction. Which has resulted in k-12 teachers, 00:02:43.000 --> 00:02:47.000 parents, university faculty and students of all ages 00:02:47.000 --> 00:02:51.000 turning to the Internet searching for online videos. 00:02:51.000 --> 00:02:56.000 And over the past decade, there has been a proliferation 00:02:56.000 --> 00:03:03.000 of websites offering online videos for stem learning. 00:03:03.000 --> 00:03:06.000 Despite the enormous amount of videos available 00:03:06.000 --> 00:03:12.000 online, Janet Bowers and colleagues summarize at least 00:03:12.000 --> 00:03:14.000 for math videos that there is surprising uniformity in 00:03:14.000 --> 00:03:21.000 presentation. Either talking head or talking head 00:03:21.000 --> 00:03:26.000 demonstrates a single step by step procedure for solving a 00:03:26.000 --> 00:03:29.000 given problem. We have this amazing technology allows 00:03:29.000 --> 00:03:34.000 students to access content from anywhere at any time. 00:03:34.000 --> 00:03:38.000 And to control the piece of learning but yet we have to 00:03:38.000 --> 00:03:40.000 fully realize its potential. And we need to imagine and 00:03:40.000 --> 00:03:44.000 create alternative 00:03:44.000 --> 00:03:49.000 models for STEM education 00:03:49.000 --> 00:03:52.000 videos now, in particular we wondered where are the 00:03:52.000 --> 00:03:55.000 students voices in these videos. Surely there had to 00:03:55.000 --> 00:04:00.000 be videos out there that brought in student thinking. 00:04:00.000 --> 00:04:05.000 And because my research area has been at the secondary 00:04:05.000 --> 00:04:09.000 school math level, we searched for K-12 online math videos in 00:04:09.000 --> 00:04:14.000 a variety of places that we 00:04:14.000 --> 00:04:18.000 thought might have produced models like projects and 00:04:18.000 --> 00:04:23.000 education repository videos. We found after reviewing 00:04:23.000 --> 00:04:29.000 hundreds of K-12 math videos only a small number of videos 00:04:29.000 --> 00:04:31.000 had student voices and we categorize those as falling 00:04:31.000 --> 00:04:36.000 into three different categories. First you saw 00:04:36.000 --> 00:04:38.000 some students take on a traditional role. They 00:04:38.000 --> 00:04:43.000 would mimic a 00:04:43.000 --> 00:04:47.000 teacher when there was dialogue and problem solving 00:04:47.000 --> 00:04:52.000 the video used animated characters and not real kids. 00:04:52.000 --> 00:04:56.000 For YouTube videos, there is a lot of kids rapping math 00:04:56.000 --> 00:04:59.000 formulas. Now, you can find some online videos that 00:04:59.000 --> 00:05:03.000 feature conceptual understanding and show 00:05:03.000 --> 00:05:07.000 students communicating their math ideas. But these have 00:05:07.000 --> 00:05:10.000 been generally created for teachers, not filmed for 00:05:10.000 --> 00:05:20.000 students to actually learn from. 00:05:20.000 --> 00:05:24.000 we found inspiration in emerging research on the use 00:05:24.000 --> 00:05:28.000 of videos with dialogues from undergraduate from different 00:05:28.000 --> 00:05:33.000 science disciplines and computer literacy. I want to 00:05:33.000 --> 00:05:38.000 highlight two of those s tudies. One was physics by 00:05:38.000 --> 00:05:41.000 Derrick Mueller. Some may know him as the creator of the 00:05:41.000 --> 00:05:47.000 awesome YouTube channel 00:05:47.000 --> 00:05:48.000 vertocism. He assigned under graduates to one of two 00:05:48.000 --> 00:05:52.000 different type video treatments. One was a 00:05:52.000 --> 00:05:54.000 monologue and the other was a 00:05:54.000 --> 00:05:58.000 dialogue. The 00:05:58.000 --> 00:06:02.000 monologue, a course is offered and in the dialogue a student 00:06:02.000 --> 00:06:07.000 voices a misconception and then eighty for 00:06:07.000 --> 00:06:13.000 a tutor and student have an exchange why that won't work 00:06:13.000 --> 00:06:17.000 and a scientific explanation is offered. And the 00:06:17.000 --> 00:06:21.000 participants in the study were given a preand post test given 00:06:21.000 --> 00:06:23.000 force concept inventory type questions. They were also 00:06:23.000 --> 00:06:26.000 interviewed. One of the interview questions was, what 00:06:26.000 --> 00:06:32.000 did you think of the video? 00:06:32.000 --> 00:06:37.000 So the students who had viewed the monologue thought it was 00:06:37.000 --> 00:06:41.000 great. It was clear, concise, easy to understand. But the 00:06:41.000 --> 00:06:46.000 students who viewed the dialogue actually found it 00:06:46.000 --> 00:06:51.000 kind of confusing. However, they were the only group that 00:06:51.000 --> 00:06:58.000 had prepost gains unlike the monologue group. In biology, 00:06:58.000 --> 00:07:02.000 there is a study again where undergraduates were assigned 00:07:02.000 --> 00:07:04.000 to monologue versus dialogue treatments. In this case the 00:07:04.000 --> 00:07:10.000 dialogue 00:07:10.000 --> 00:07:15.000 was unscripted where in muller 's case he used scripted 00:07:15.000 --> 00:07:19.000 videos. This was around the topic of molecular die fusion. 00:07:19.000 --> 00:07:22.000 And the dialogue group outperformed those in the 00:07:22.000 --> 00:07:25.000 monologue group. And then there was a follow-up study to 00:07:25.000 --> 00:07:31.000 find out why that was the case . They did a s econdary 00:07:31.000 --> 00:07:36.000 analysis on this same data. And found that in 00:07:36.000 --> 00:07:41.000 the dialoguic students often engaged in problem solving 00:07:41.000 --> 00:07:43.000 versus copying solutions. And they repeated and elaborated 00:07:43.000 --> 00:07:47.000 more statements made by the student than the tutor, even 00:07:47.000 --> 00:07:51.000 when the student made incorrect statements. So the 00:07:51.000 --> 00:07:56.000 authors concluded that the crucial element of a dialoguic 00:07:56.000 --> 00:07:58.000 video is an authentic learner that displays confusion and 00:07:58.000 --> 00:08:02.000 asks questions. 00:08:02.000 --> 00:08:07.000 So our aim in creating our videos for our project was to 00:08:07.000 --> 00:08:11.000 feature pairs of students engaging in dialogue where 00:08:11.000 --> 00:08:16.000 dialogue is a conversation that involves the quality of 00:08:16.000 --> 00:08:22.000 inquiry which aims at developing new insights and 00:08:22.000 --> 00:08:26.000 learning. And we extended this previously search by 00:08:26.000 --> 00:08:31.000 bringing these dialogic v ideos into secondary pact 00:08:31.000 --> 00:08:38.000 learning by using pairs of students as opposed to 00:08:38.000 --> 00:08:41.000 student-tutor pairs and filming sequences of videos of 00:08:41.000 --> 00:08:44.000 the statement students learning over time. We have 00:08:44.000 --> 00:08:47.000 to contribution to the expansion of different models 00:08:47.000 --> 00:08:52.000 of what is possible in online videos. Now, the rest of the 00:08:52.000 --> 00:08:55.000 talk is organized into two main sections. First 00:08:55.000 --> 00:09:00.000 development and then research and theory. 00:09:00.000 --> 00:09:07.000 So we call ourselves project math talk. And our videos can 00:09:07.000 --> 00:09:14.000 be found at mathtalk.org. In a previous exploratory grant, 00:09:14.000 --> 00:09:18.000 we created two units of videos . And in our current NSF 00:09:18.000 --> 00:09:23.000 grant we are developing six more units for different 00:09:23.000 --> 00:09:28.000 algebra 1 and 2 topics. And each video unit is 00:09:28.000 --> 00:09:31.000 broken down into about 7 lessons and has about 40 short 00:09:31.000 --> 00:09:36.000 videos for each unit. So I would like to introduce you to 00:09:36.000 --> 00:09:40.000 our videos by focusing on two features. First is the 00:09:40.000 --> 00:09:46.000 unscripted dialogue. And I'm going to be showing you two 00:09:46.000 --> 00:09:52.000 video clips from these two students. We call them the 00:09:52.000 --> 00:09:55.000 talent. We're very Hollywood. Sasha and keoni are grade 9 00:09:55.000 --> 00:09:58.000 and 10 students. And they're working on a task in which 00:09:58.000 --> 00:10:01.000 they're trying to create a 00:10:01.000 --> 00:10:06.000 parabola from its geometric definition. That definition 00:10:06.000 --> 00:10:09.000 is that a p arabola is a set of points that are equal 00:10:09.000 --> 00:10:15.000 distance from a fixed point called the focus and a fixed 00:10:15.000 --> 00:10:22.000 line called the directrix. To solve this task, you need to 00:10:22.000 --> 00:10:30.000 create a focus and a directrix and make sure that they're the 00:10:30.000 --> 00:10:33.000 same distance from the focus as their to the directrix. 00:10:33.000 --> 00:10:37.000 I'm superimposing the solution that they came to. They 00:10:37.000 --> 00:10:41.000 started out with a lot of false starts and confusion. 00:10:41.000 --> 00:10:44.000 They had -- they talked about 00:10:44.000 --> 00:10:47.000 parabolas in their regular math class. They have had 00:10:47.000 --> 00:10:52.000 never seen this definition or this task. They started 00:10:52.000 --> 00:10:55.000 tribing what they knew about parabola saying it is like a V 00:10:55.000 --> 00:10:57.000 or a U shape on a graph. And when they placed their first 00:10:57.000 --> 00:11:04.000 point, they 00:11:04.000 --> 00:11:06.000 used the mid point between the focus and the directrix and 00:11:06.000 --> 00:11:09.000 explained why it fit the definition, that the distance 00:11:09.000 --> 00:11:16.000 was between their point and the focus as it was between 00:11:16.000 --> 00:11:20.000 their point and the directrix. And I'm going to show you a 00:11:20.000 --> 00:11:24.000 two-minute clip where keoni places a new point. It is 00:11:24.000 --> 00:11:27.000 right under his finger. You can't see it in that little 00:11:27.000 --> 00:11:32.000 snapshot there. It is right to the -- right below the 00:11:32.000 --> 00:11:34.000 correct point that they had placed. And they disagree 00:11:34.000 --> 00:11:39.000 about whether it is correct or not. It is actually not 00:11:39.000 --> 00:11:42.000 correct. But keoni thinks it is and Sasha disagrees with 00:11:42.000 --> 00:11:47.000 him. Even during viewing this two-minute video or I'll give 00:11:47.000 --> 00:11:50.000 you time afterwards, just enter into chat if you are so 00:11:50.000 --> 00:11:54.000 inclined anything that you notice about the video. Might 00:11:54.000 --> 00:11:57.000 be about the students, their 00:11:57.000 --> 00:12:00.000 interactions, the off-screen teacher, the nature of their 00:12:00.000 --> 00:12:02.000 confusion or anything else. All right. So here goes the 00:12:02.000 --> 00:12:05.000 video. 00:12:05.000 --> 00:12:07.000 » It looks equal. Is it right 00:12:07.000 --> 00:12:10.000 there? 00:12:10.000 --> 00:12:16.000 Okay. 00:12:16.000 --> 00:12:19.000 Then is -- and then it's not. You know. 00:12:19.000 --> 00:12:23.000 » No. » Hold on. Okay. So there's 00:12:23.000 --> 00:12:25.000 that and then t here. Oh, it is too short. It is too short 00:12:25.000 --> 00:12:33.000 . 00:12:33.000 --> 00:12:37.000 [Laughter] » What do you think, 00:12:37.000 --> 00:12:41.000 keoni. » Well, they are both sort of 00:12:41.000 --> 00:12:47.000 equal distance f rom -- so this is equal -- this distance 00:12:47.000 --> 00:12:55.000 here from one of our points to the directrix is the same as 00:12:55.000 --> 00:13:06.000 the distance from the point of the focus. And then this 00:13:06.000 --> 00:13:08.000 point, the distance from the d irectrix to the point is equal 00:13:08.000 --> 00:13:11.000 to 00:13:11.000 --> 00:13:12.000 the 00:13:12.000 --> 00:13:14.000 -- » Cheater. 00:13:14.000 --> 00:13:17.000 » Focus. 00:13:17.000 --> 00:13:23.000 » He cheated. Actually. 00:13:23.000 --> 00:13:27.000 » If they are both equal distance, we have a p arabola. 00:13:27.000 --> 00:13:30.000 » Huh? 00:13:30.000 --> 00:13:34.000 » If this is equal to that and this is -- 00:13:34.000 --> 00:13:37.000 » How many points do you think are on the p arabola. 00:13:37.000 --> 00:13:41.000 » Well, at least two. Probably like -- you know, 00:13:41.000 --> 00:13:46.000 like with the -- it is like continuous. So it should keep 00:13:46.000 --> 00:13:49.000 going on. » How many points are on the 00:13:49.000 --> 00:13:52.000 parabola. » At least three. Because we 00:13:52.000 --> 00:13:55.000 have a vertex and the two -- yeah. 00:13:55.000 --> 00:14:00.000 » If there -- I think you have 00:14:00.000 --> 00:14:04.000 to try to find. [ Indiscernible] 00:14:04.000 --> 00:14:05.000 » Dot, dot, dot, dot, dot, dot . 00:14:05.000 --> 00:14:10.000 » What? 00:14:10.000 --> 00:14:12.000 » Let's try one of those. » And then dot, dot, dot, dot, 00:14:12.000 --> 00:14:16.000 dot. » Pick one and see if it fits 00:14:16.000 --> 00:14:17.000 the definition. » Well, do you want to be 00:14:17.000 --> 00:14:21.000 perfect? » Yes. 00:14:21.000 --> 00:14:22.000 » Okay. » They should be. 00:14:22.000 --> 00:14:24.000 » Definition. Pick one of the points. 00:14:24.000 --> 00:14:28.000 » So this point. » That one -- 00:14:28.000 --> 00:14:30.000 » Yeah. What are you talking about? Do it like that one. 00:14:30.000 --> 00:14:32.000 » Is that the same distance to your line as it is to the 00:14:32.000 --> 00:14:36.000 focus. » Huh-uh. 00:14:36.000 --> 00:14:37.000 » I guess not. » Why do you say you guess not 00:14:37.000 --> 00:14:39.000 . » Focus is -- 00:14:39.000 --> 00:14:42.000 » Yeah. » And then -- 00:14:42.000 --> 00:14:46.000 » That is not the same. » There you go. 00:14:46.000 --> 00:14:48.000 » It doesn't work. 00:14:48.000 --> 00:14:50.000 » I see that. 00:14:50.000 --> 00:14:53.000 » JOANNE LOBATO, Ph.D.: So I 00:14:53.000 --> 00:14:56.000 noticed a few people from entered really awesome 00:14:56.000 --> 00:14:58.000 observations about the video into chat. I would like to 00:14:58.000 --> 00:15:03.000 give another minute or two for people to enter and have a 00:15:03.000 --> 00:15:05.000 chance to read other people's observations. Anything you 00:15:05.000 --> 00:15:35.000 noticed about the video. 00:15:53.000 --> 00:15:57.000 » JOANNE LOBATO, Ph.D.: I've 00:15:57.000 --> 00:15:59.000 noticed in the chat are how comfortable they feel with 00:15:59.000 --> 00:16:01.000 each other 00:16:01.000 --> 00:16:04.000 experimenting. They were friends outside of this. And 00:16:04.000 --> 00:16:11.000 I think that really helped with them listening to each 00:16:11.000 --> 00:16:16.000 other. Also someone noted that the definition is sort of 00:16:16.000 --> 00:16:20.000 coming into focus. It is not in focus yet, especially for 00:16:20.000 --> 00:16:24.000 keoni. And I think this is the role of the teacher. Not 00:16:24.000 --> 00:16:26.000 so much to give them a lot of information but redirecting 00:16:26.000 --> 00:16:30.000 their attention and guiding them. And you may have 00:16:30.000 --> 00:16:33.000 noticed that we have some annotations here, some labels 00:16:33.000 --> 00:16:39.000 on the 00:16:39.000 --> 00:16:44.000 videos. Our videos are not raw. We edit them. We an 00:16:44.000 --> 00:16:47.000 Tate, put labels o n. And we also summarize -- we have 00:16:47.000 --> 00:16:52.000 animated summaries. I'm going to show you one of them. So 00:16:52.000 --> 00:16:57.000 in this one-minute video, I want you to watch for the 00:16:57.000 --> 00:17:02.000 voiced-over summary at the end . And we do this to really 00:17:02.000 --> 00:17:08.000 highlight the ideas for the viewers but we try to stay 00:17:08.000 --> 00:17:10.000 close to the ideas and we aactually use keoni's hand in 00:17:10.000 --> 00:17:13.000 the animation. This one- minute clip comes soon after 00:17:13.000 --> 00:17:15.000 the video that you just watched. Now he seems to be 00:17:15.000 --> 00:17:20.000 paying more attention to the definition and correctly uses 00:17:20.000 --> 00:17:22.000 it to create a new method to place two more points on the 00:17:22.000 --> 00:17:28.000 parabola. 00:17:28.000 --> 00:17:41.000 » And then we can put our 00:17:41.000 --> 00:17:47.000 point -- let's make it. Three inches away from that. 00:17:47.000 --> 00:17:55.000 [ 00:17:55.000 --> 00:18:01.000 Indiscernible] just going to directrix. 00:18:01.000 --> 00:18:05.000 So now both of our points. » Is that -- 00:18:05.000 --> 00:18:09.000 » The same. Yeah. [Laughter] 00:18:09.000 --> 00:18:14.000 » Two points. Okay. A point 00:18:14.000 --> 00:18:16.000 to the focus is 3 inches. And a point to the directrix is 3 00:18:16.000 --> 00:18:19.000 inches. Same over here. 00:18:19.000 --> 00:18:23.000 Yeah. » Uh-huh. 00:18:23.000 --> 00:18:28.000 » Has discovered a new method. He first places the focus 3 00:18:28.000 --> 00:18:33.000 inches from the directrix. Then he places a point three 00:18:33.000 --> 00:18:38.000 inches to one side of the focus and the point three 00:18:38.000 --> 00:18:43.000 inches to the other side of the focus. These two points 00:18:43.000 --> 00:18:46.000 work because each point is the same distance from the focus 00:18:46.000 --> 00:18:50.000 as it is from the 00:18:50.000 --> 00:18:52.000 directrix, namely 3 inches. 00:18:52.000 --> 00:18:57.000 » JOANNE LOBATO, Ph.D.: And 00:18:57.000 --> 00:19:01.000 before we -- I talk about our research, I just want to 00:19:01.000 --> 00:19:05.000 mention what it has been like filming prepandemic and now. 00:19:05.000 --> 00:19:09.000 Before the pandemic, we had set up a film studio at our 00:19:09.000 --> 00:19:14.000 research center. And now we are just about ready to film. 00:19:14.000 --> 00:19:18.000 We have created a Zoom-based approach that uses the white 00:19:18.000 --> 00:19:20.000 board explain everything. And we will be delivering these 00:19:20.000 --> 00:19:27.000 care 00:19:27.000 --> 00:19:33.000 packages to the talent that will be participated. And it 00:19:33.000 --> 00:19:40.000 includes an individual green screen, iPad, microphone and 00:19:40.000 --> 00:19:46.000 web cam. In the pretty types we have type -- prototypes we 00:19:46.000 --> 00:19:48.000 have been able to get pretty close to the look of the 00:19:48.000 --> 00:19:52.000 original videos. I want to share with you the results of 00:19:52.000 --> 00:19:56.000 three of our studies. First we would like to define this 00:19:56.000 --> 00:20:00.000 term that I have been using, vicarious learning. So this 00:20:00.000 --> 00:20:07.000 was a term that 00:20:07.000 --> 00:20:10.000 b andora introduces in the 1960s. We are following 00:20:10.000 --> 00:20:13.000 colleagues definition of vicarious l earning meaning 00:20:13.000 --> 00:20:17.000 learning by observing and engaging with video or audio 00:20:17.000 --> 00:20:22.000 tape presentations of other people engaged in 00:20:22.000 --> 00:20:28.000 learning. So you have seen Sasha and keoni engaged in 00:20:28.000 --> 00:20:31.000 dialogue. And views of that dialogue 00:20:31.000 --> 00:20:36.000 are do I log indirectly, vicariously. So the students 00:20:36.000 --> 00:20:40.000 in the videos are called the talent. And the viewer 00:20:40.000 --> 00:20:45.000 engaged with their dialogue is called the vicarious learner. 00:20:45.000 --> 00:20:50.000 We have taken our videos out to high schools and actually 00:20:50.000 --> 00:20:52.000 used them with undergraduates in a number of studies we used 00:20:52.000 --> 00:20:54.000 students in focus testing to help develop the look for our 00:20:54.000 --> 00:21:01.000 videos. 00:21:01.000 --> 00:21:04.000 And also one study we put one lesson in front of a 00:21:04.000 --> 00:21:08.000 larger number of students and then followed a smaller number 00:21:08.000 --> 00:21:14.000 of students as they worked through the entire 00:21:14.000 --> 00:21:16.000 parabolas unit. I had a student do his dissertation 00:21:16.000 --> 00:21:20.000 with math majors and we will be sharing some of thinks 00:21:20.000 --> 00:21:25.000 findings later. So the first research finding is about how 00:21:25.000 --> 00:21:33.000 the vicarious learners oriented towards the 00:21:33.000 --> 00:21:36.000 talent. But first I want to share a theoretical idea from 00:21:36.000 --> 00:21:40.000 the vicarious learning project which was one of the original 00:21:40.000 --> 00:21:48.000 projects working in this space . And they conceived of a 00:21:48.000 --> 00:21:52.000 vicarious learner as a voyer to dialogue. And said that 00:21:52.000 --> 00:21:57.000 vicarious learning involved something that they called 00:21:57.000 --> 00:22:03.000 epistemic detachment. There was an an 00:22:03.000 --> 00:22:07.000 an emotional and -- this could be helpful because the 00:22:07.000 --> 00:22:10.000 vicarious learners are not involved in defending their 00:22:10.000 --> 00:22:14.000 own position then they might be better able to attend to 00:22:14.000 --> 00:22:17.000 what was being said and take on the perspective of each 00:22:17.000 --> 00:22:24.000 person involved in that dialogue. 00:22:24.000 --> 00:22:27.000 I found some evidence to indicate the vicarious 00:22:27.000 --> 00:22:31.000 learning could proceed in just the opposite way. That there 00:22:31.000 --> 00:22:34.000 would be emotional investment instead of an epistemic 00:22:34.000 --> 00:22:37.000 detachment and that the vicarious l earners could 00:22:37.000 --> 00:22:41.000 orient towards the talent as if they were in a 00:22:41.000 --> 00:22:47.000 collaborative group with them, which we call quasi 00:22:47.000 --> 00:22:52.000 collaboration rather than acting like 00:22:52.000 --> 00:22:55.000 voyeurs. And this comes from investigating the students 00:22:55.000 --> 00:22:59.000 over time as they work through the entire unit of videos. 00:22:59.000 --> 00:23:03.000 And we categorize five categories of behavior that 00:23:03.000 --> 00:23:08.000 were consistent with the quasi collaborative stance and 00:23:08.000 --> 00:23:13.000 emotional attachment to the talent. So let me just 00:23:13.000 --> 00:23:21.000 briefly share three categories of behavior with 00:23:21.000 --> 00:23:23.000 you. The first is that the vicarious l earners frequently 00:23:23.000 --> 00:23:26.000 characterized Sasha and 00:23:26.000 --> 00:23:30.000 k eoni's 00:23:30.000 --> 00:23:35.000 mathematical personalities. Sasha is the Jenner. Shortcut 00:23:35.000 --> 00:23:39.000 finder. Keoni is methodical and careful and repetitive. 00:23:39.000 --> 00:23:43.000 And then they went on to align each of themselves with each 00:23:43.000 --> 00:23:47.000 one of the mathematical personalities of the talent. 00:23:47.000 --> 00:23:51.000 We Lynn asaid I'm like keoni and you're Sasha because I 00:23:51.000 --> 00:23:54.000 always want to go the long way . And 00:23:54.000 --> 00:23:57.000 desiree yeah because she, Belinda, always wants to do 00:23:57.000 --> 00:24:03.000 something bigger and I want to do it the short way right away 00:24:03.000 --> 00:24:06.000 , just like Sasha. Now, we can't say that they're in a 00:24:06.000 --> 00:24:10.000 collaborative group with the talent because the talent aren 00:24:10.000 --> 00:24:15.000 't even in the same room with them. But argues that central 00:24:15.000 --> 00:24:19.000 to collaboration is a process in which students organize 00:24:19.000 --> 00:24:24.000 themselves to engage in coordinated activity. 00:24:24.000 --> 00:24:28.000 she talked about paying attention to ideas of all 00:24:28.000 --> 00:24:33.000 group members. Comparing one' s work to others. And keeping 00:24:33.000 --> 00:24:36.000 track of what has been said. And that's exactly what 00:24:36.000 --> 00:24:42.000 happened. They -- the vicarious learners would say 00:24:42.000 --> 00:24:44.000 things like she made the same mistake as us, referring to 00:24:44.000 --> 00:24:48.000 Sasha. Or saying things like she said the same thing as you 00:24:48.000 --> 00:24:56.000 . But they have new edits too . 00:24:56.000 --> 00:25:00.000 Finally the vicarious learners made several statements that 00:25:00.000 --> 00:25:04.000 indicated they felt part of a community with the talent. 00:25:04.000 --> 00:25:09.000 And believed that they were struggling together. A common 00:25:09.000 --> 00:25:13.000 theme was the pain of feeling alone in a math classroom when 00:25:13.000 --> 00:25:17.000 one is confused. And that shared confusion via the video 00:25:17.000 --> 00:25:20.000 helps alleviate that pain. 00:25:20.000 --> 00:25:23.000 I'm going to share a o ne- minute video from the 00:25:23.000 --> 00:25:27.000 vicarious learners. This occurred at the end of a 00:25:27.000 --> 00:25:31.000 research session. They had just watched a video where 00:25:31.000 --> 00:25:33.000 keoni was quite confused and the researcher asked if they 00:25:33.000 --> 00:25:37.000 would prefer to have videos without confusion. They were 00:25:37.000 --> 00:25:40.000 adamant that they preferred the confused ones, as they 00:25:40.000 --> 00:25:46.000 called it. And this in video, watch for one of the students 00:25:46.000 --> 00:25:49.000 to share how she feels like an alien in her math class when 00:25:49.000 --> 00:25:54.000 she is confused. » If you had a choice a Sasha 00:25:54.000 --> 00:25:57.000 and keoni who had that confusion about the focus and 00:25:57.000 --> 00:26:01.000 they figured it out versus kids who just knew it was 00:26:01.000 --> 00:26:03.000 wrong and they knew how to place it, which would you 00:26:03.000 --> 00:26:05.000 rather watch? » [ 00:26:05.000 --> 00:26:08.000 Indiscernible] » How come? More confused. 00:26:08.000 --> 00:26:11.000 » Because you're learning with them. 00:26:11.000 --> 00:26:15.000 » Oh. » You like that. 00:26:15.000 --> 00:26:17.000 » It helps because you feel like you're the only one. 00:26:17.000 --> 00:26:19.000 » Yeah. » And you're learning -- 00:26:19.000 --> 00:26:21.000 » Alien. » You're learning step by 00:26:21.000 --> 00:26:22.000 stuff. » You feel like an alien in 00:26:22.000 --> 00:26:25.000 the classroom. » Yeah. 00:26:25.000 --> 00:26:29.000 » Oh, no. » I felt like it was -- like 00:26:29.000 --> 00:26:31.000 he was giving me an example and I felt like I was the only 00:26:31.000 --> 00:26:33.000 alien t here. There is always someone confused at some point 00:26:33.000 --> 00:26:35.000 . 00:26:35.000 --> 00:26:39.000 » JOANNE LOBATO, Ph.D.: And in 00:26:39.000 --> 00:26:44.000 the later session, she reflects again on confusion 00:26:44.000 --> 00:26:48.000 and says, you know what I get really confused, I get 00:26:48.000 --> 00:26:52.000 isolated. Like I'm the only one. But knowing that she, 00:26:52.000 --> 00:26:56.000 meaning Sasha is confused too, we're both 00:26:56.000 --> 00:26:59.000 confused. Seeing other kids being confused, you feel like 00:26:59.000 --> 00:27:03.000 you're part of a community of learners. I know most of you 00:27:03.000 --> 00:27:07.000 do research at the undergraduate l evel. For me 00:27:07.000 --> 00:27:10.000 this research suggests other questions that could be 00:27:10.000 --> 00:27:13.000 researched at the 00:27:13.000 --> 00:27:17.000 undergraduate level. Like what they find comfort in 00:27:17.000 --> 00:27:22.000 viewing videos of their peers confusion. Mike foster is 00:27:22.000 --> 00:27:26.000 designing a dissertation study . As part of it he will be 00:27:26.000 --> 00:27:30.000 working with college algebra students at our university. 00:27:30.000 --> 00:27:34.000 And we will be comparing their orientation towards the talent 00:27:34.000 --> 00:27:41.000 in unscripted versus scripted dialogic videos. 00:27:41.000 --> 00:27:45.000 The secondary search finding comes from another 00:27:45.000 --> 00:27:49.000 dissertation that came out of the project by C David Walters 00:27:49.000 --> 00:27:53.000 . He worked with intergraduate math majors. 00:27:53.000 --> 00:27:56.000 One finding had to do with decent e ntering. So decent 00:27:56.000 --> 00:27:59.000 entering is a peer study in motion that involves taking on 00:27:59.000 --> 00:28:04.000 perspectives other than your own. And in particular 00:28:04.000 --> 00:28:08.000 understanding how your -- how someone else's perspective 00:28:08.000 --> 00:28:12.000 differs from your own. This is really important for the 00:28:12.000 --> 00:28:14.000 practice of argumentation in scientific and mathematical 00:28:14.000 --> 00:28:20.000 demands. 00:28:20.000 --> 00:28:23.000 Also comment on how it is important for teachers. 00:28:23.000 --> 00:28:26.000 Teachers who can decenter are able to distinguish their 00:28:26.000 --> 00:28:30.000 students' reasoning from their own, which makes them more 00:28:30.000 --> 00:28:32.000 likely to be able to leverage students thinking productively 00:28:32.000 --> 00:28:39.000 while teaching. 00:28:39.000 --> 00:28:42.000 So C David Walters did a study with seven recent graduates. 00:28:42.000 --> 00:28:46.000 They were all math majors. Just before they entered a 00:28:46.000 --> 00:28:51.000 secondary teaching credential program. 00:28:51.000 --> 00:28:57.000 And he ran a mini course in the summer with them, 12 hours 00:28:57.000 --> 00:28:59.000 . With the use of mathtalk videos from this unit 00:28:59.000 --> 00:29:04.000 regularly. And he investigated many things. But 00:29:04.000 --> 00:29:08.000 one thing is shifts in their - - the undergraduates ability 00:29:08.000 --> 00:29:12.000 to decent enter. And I just want to share a brief example. 00:29:12.000 --> 00:29:18.000 This came from a student that he called Marshall. It was in 00:29:18.000 --> 00:29:24.000 the post interview. After the course had ended. And he was 00:29:24.000 --> 00:29:28.000 asked to use this definition a parabola to derive the 00:29:28.000 --> 00:29:33.000 equation of a general parabola . They had not covered this 00:29:33.000 --> 00:29:36.000 task in the course. It turns out that Sasha and keoni had 00:29:36.000 --> 00:29:41.000 solved this task but it had not been shared with the 00:29:41.000 --> 00:29:46.000 participants. And so Marshall initially uses his knowledge 00:29:46.000 --> 00:29:49.000 of a base equation, along with translation. He comes up with 00:29:49.000 --> 00:29:53.000 a correct equation. But he doesn't end up referring to 00:29:53.000 --> 00:29:57.000 the definition. The interviewer at point says can 00:29:57.000 --> 00:30:04.000 you point out where you used the definition of a 00:30:04.000 --> 00:30:08.000 parabola to find that. I didn 't. I required on my prior 00:30:08.000 --> 00:30:12.000 knowledge. This one he starts by attending to the definition 00:30:12.000 --> 00:30:17.000 labels the focus and directrix . But then moves away from it 00:30:17.000 --> 00:30:22.000 . Uses a distance formula. And then when asked about 00:30:22.000 --> 00:30:24.000 geometric -- information has to do a bunch of algebraic 00:30:24.000 --> 00:30:28.000 calculations to come up with that information instead of 00:30:28.000 --> 00:30:35.000 using it as sort of the grounding point to start from. 00:30:35.000 --> 00:30:39.000 But then in a third attempt, the researcher asked Marshall, 00:30:39.000 --> 00:30:43.000 what does Marshall think Sasha and keoni could do. Again, he 00:30:43.000 --> 00:30:47.000 had not seen them solve the problem. Although we have 00:30:47.000 --> 00:30:52.000 tape of them doing it. Keoni when asked this, he was able 00:30:52.000 --> 00:30:55.000 to exactly predict the way that they would do it. I'm 00:30:55.000 --> 00:31:00.000 just sort of highlighting here the similarities between 00:31:00.000 --> 00:31:04.000 Marshall's work and what Sasha and keoni actually did. 00:31:04.000 --> 00:31:10.000 So you don't need to read all of that. Just kind of seeing 00:31:10.000 --> 00:31:15.000 the similarities. And not only that, but he was able to 00:31:15.000 --> 00:31:17.000 explain -- identify what Sasha and keoni might understand and 00:31:17.000 --> 00:31:21.000 what they might have difficulty understanding which 00:31:21.000 --> 00:31:27.000 we think provides evidence 00:31:27.000 --> 00:31:32.000 of decentering. I'm going to play a quick video. 00:31:32.000 --> 00:31:36.000 » This side of the triangle 00:31:36.000 --> 00:31:39.000 as Xh. I think they would have -- as they look at that 00:31:39.000 --> 00:31:45.000 distance, they would have the Y. 00:31:45.000 --> 00:31:48.000 Minus K to get up to the v ertex. And then take away a 00:31:48.000 --> 00:31:52.000 little more. They need to take away P. So you have this 00:31:52.000 --> 00:31:56.000 whole thing Y. So if you take away K you get all the way up 00:31:56.000 --> 00:31:59.000 to the focus. And if you add P back in, you get back down 00:31:59.000 --> 00:32:03.000 to the directrix, that's what they w anted. There the point 00:32:03.000 --> 00:32:08.000 to the directrix. » JOANNE LOBATO, Ph.D.: So 00:32:08.000 --> 00:32:15.000 when prompted to think about Sasha and keoni, Marshall 00:32:15.000 --> 00:32:19.000 seemed to be able to decenter by shifting his point of view. 00:32:19.000 --> 00:32:22.000 We think these videos of the talent over time helps support 00:32:22.000 --> 00:32:27.000 that decentering. So this makes me think about questions 00:32:27.000 --> 00:32:31.000 for deeper research. You know , could dialogic videos be 00:32:31.000 --> 00:32:37.000 used to model important scientific and math Matt 00:32:37.000 --> 00:32:46.000 campaign practices like persistence in problem 00:32:46.000 --> 00:32:49.000 solving, and could vicarious learners improving those 00:32:49.000 --> 00:32:51.000 practices engaging with such videos? I think there are a 00:32:51.000 --> 00:32:56.000 lot of unanswered and important questions to be 00:32:56.000 --> 00:33:01.000 pursued. And in the final research finding that I want 00:33:01.000 --> 00:33:05.000 to share with you, we discovered a variety of ways 00:33:05.000 --> 00:33:10.000 that vicarious -- vicarious learners a pproached dialogic 00:33:10.000 --> 00:33:12.000 videos. And this comes from the study in which we put a 00:33:12.000 --> 00:33:15.000 fairly 00:33:15.000 --> 00:33:19.000 large number of high school students for a core data study 00:33:19.000 --> 00:33:23.000 in front of one lesson, the lesson on 00:33:23.000 --> 00:33:30.000 parabolas with Sasha and 00:33:30.000 --> 00:33:36.000 keoni you have been watched. They came from a traditional 00:33:36.000 --> 00:33:38.000 algebra 1. They watched Sasha and keoni and then had them 00:33:38.000 --> 00:33:43.000 solve 00:33:43.000 --> 00:33:45.000 the same task. It is challenging enough even after 00:33:45.000 --> 00:33:49.000 watching the videos for the vicarious learners. And we 00:33:49.000 --> 00:33:54.000 found that all engaged with the videos and appropriated 00:33:54.000 --> 00:33:57.000 something but their approach is different and we called 00:33:57.000 --> 00:34:00.000 them games that the vicarious learners played. We 00:34:00.000 --> 00:34:03.000 identified four of them, which I'll convey in just a minute. 00:34:03.000 --> 00:34:07.000 And that the games had consequences for the problem 00:34:07.000 --> 00:34:15.000 solving behavior of the vicarious learners. 00:34:15.000 --> 00:34:19.000 So we used -- adapted game -- game board theory, like board 00:34:19.000 --> 00:34:22.000 games in which players behavior is goal directed and 00:34:22.000 --> 00:34:24.000 guided by a set of rules that regulate their activity in the 00:34:24.000 --> 00:34:28.000 game, their use of pieces in the games and their actions 00:34:28.000 --> 00:34:32.000 towards other players. We inferred ways in which the 00:34:32.000 --> 00:34:37.000 vicarious learners' behavior appeared to be regulated by 00:34:37.000 --> 00:34:39.000 rules governing the activity of creating a parabola, what 00:34:39.000 --> 00:34:42.000 information they attended to in the videos and the way that 00:34:42.000 --> 00:34:45.000 they justified points being on their 00:34:45.000 --> 00:34:50.000 parabola or not to the researcher. And we inferred 00:34:50.000 --> 00:34:57.000 four g ames. The first game we called the definition game. 00:34:57.000 --> 00:35:00.000 And fortunately the majority of the l earners and the 00:35:00.000 --> 00:35:04.000 talent. They attended to the definition of the parabola in 00:35:04.000 --> 00:35:07.000 the video. They used that definite Tigs to create 00:35:07.000 --> 00:35:12.000 justified p oints. The definition of the 00:35:12.000 --> 00:35:16.000 parabola guided their behavior . But, you know, even though 00:35:16.000 --> 00:35:19.000 the majority played the definition game, a number of 00:35:19.000 --> 00:35:25.000 other students played another game called the concept image 00:35:25.000 --> 00:35:27.000 game. And it was striking to us that even though the 00:35:27.000 --> 00:35:34.000 definition a 00:35:34.000 --> 00:35:38.000 par abola was stated 41 times some ignored it and relied 00:35:38.000 --> 00:35:43.000 only on their concept image of a 00:35:43.000 --> 00:35:45.000 parabola as a U-shaped on a grid. They attended to grid 00:35:45.000 --> 00:35:49.000 like features of the talent's drawings. Instead of 00:35:49.000 --> 00:35:54.000 attending to the definition of a 00:35:54.000 --> 00:35:56.000 parabola they paid attention to the line that's Sasha and 00:35:56.000 --> 00:36:00.000 keoni drew and different measurements they took and 00:36:00.000 --> 00:36:04.000 used those to create points that fit their concept image 00:36:04.000 --> 00:36:08.000 of an ever widening U curve even when it resulted in point 00:36:08.000 --> 00:36:14.000 that's were incorrect and didn 't fit the definition. 00:36:14.000 --> 00:36:17.000 Another game is the procedure game. These students seemed 00:36:17.000 --> 00:36:23.000 focused on identifying a set of steps to follow from the 00:36:23.000 --> 00:36:27.000 videos. And it resulted in them often making ancillary 00:36:27.000 --> 00:36:34.000 details like the length of the directrix or the distance 00:36:34.000 --> 00:36:36.000 between the parallel lines. And one peer of the vicarious 00:36:36.000 --> 00:36:40.000 learners seemed to interpret the goal as providing feedback 00:36:40.000 --> 00:36:43.000 to our research team on the design of our videos. They 00:36:43.000 --> 00:36:46.000 gave us advice on design elements like color and sound. 00:36:46.000 --> 00:36:50.000 And this was based on their own experience of creating 00:36:50.000 --> 00:36:53.000 YouTube videos. But when pressed to solve the 00:36:53.000 --> 00:36:59.000 mathematical task they then shifted to the concept image 00:36:59.000 --> 00:37:02.000 game. So I think this research on games suggests 00:37:02.000 --> 00:37:05.000 some other questions for both our teaching and research. 00:37:05.000 --> 00:37:09.000 How should we frame videos that embody a different way of 00:37:09.000 --> 00:37:14.000 engaging with math or science that has marked students' 00:37:14.000 --> 00:37:17.000 previous experiences. And can we create or use online 00:37:17.000 --> 00:37:21.000 surrounds for alternative video that's could 00:37:21.000 --> 00:37:25.000 productively support their use by both framing the videos and 00:37:25.000 --> 00:37:29.000 guiding discussions of the videos in helping vicarious 00:37:29.000 --> 00:37:33.000 learners attend to what is both, you know, important to 00:37:33.000 --> 00:37:38.000 notice in these videos. So just a quick thanks to other 00:37:38.000 --> 00:37:43.000 members of my research team. And now I would like to open 00:37:43.000 --> 00:37:47.000 it up with help from Joe of any questions that you have. 00:37:47.000 --> 00:37:50.000 But also I would love to hear comments about the work and 00:37:50.000 --> 00:37:52.000 also connections to your own work. 00:37:52.000 --> 00:37:57.000 » JOE DAUER: Great. Thank you 00:37:57.000 --> 00:38:01.000 so much, Joanne. This was fantastic. And so we have a 00:38:01.000 --> 00:38:04.000 number of questions. And I wanted to start off with the 00:38:04.000 --> 00:38:09.000 few questions that were kind of more about the structure -- 00:38:09.000 --> 00:38:12.000 the structure. So more like the -- maybe softball 00:38:12.000 --> 00:38:15.000 questions. Like what is the l ength -- there are three that 00:38:15.000 --> 00:38:20.000 fit into this. What is the length of the videos. Did the 00:38:20.000 --> 00:38:23.000 l earners watch it in pairs also and is there value there. 00:38:23.000 --> 00:38:24.000 And did you write the scripts? 00:38:24.000 --> 00:38:29.000 » JOANNE LOBATO, Ph.D.: So all 00:38:29.000 --> 00:38:33.000 of our videos are unscripted. So the dialogue is just 00:38:33.000 --> 00:38:37.000 natural between kids. But what we do 00:38:37.000 --> 00:38:41.000 afterwards is we, you know, edit the videos. And I guess 00:38:41.000 --> 00:38:43.000 that's a kind of script, that we're putting together a story 00:38:43.000 --> 00:38:47.000 line afterwards. 00:38:47.000 --> 00:38:52.000 So in our videos, if you go to our website, you will see that 00:38:52.000 --> 00:38:56.000 each lesson is broken into four to seven short videos. 00:38:56.000 --> 00:39:00.000 And each video is called an episode. And it is between 00:39:00.000 --> 00:39:04.000 two and ten minutes long. And we actually use different 00:39:04.000 --> 00:39:08.000 video types for those episodes . Because our emphasis is 00:39:08.000 --> 00:39:11.000 really on problem solving, not procedural knowledge. We have 00:39:11.000 --> 00:39:17.000 a making sense type video that starts a lesson. Where the 00:39:17.000 --> 00:39:20.000 talent are just comprehending the problem situation. And 00:39:20.000 --> 00:39:23.000 then. They have an exploring episode where they're actually 00:39:23.000 --> 00:39:26.000 solving the problem. And then there's a reflecting video 00:39:26.000 --> 00:39:29.000 where they look back on what they have done and explain it 00:39:29.000 --> 00:39:34.000 again, make connections. And then there's a repeating your 00:39:34.000 --> 00:39:37.000 reasoning which uses a pair task. It tells the vicarious 00:39:37.000 --> 00:39:39.000 learners to stop the video and try the problem on their own 00:39:39.000 --> 00:39:44.000 and then resume the video. So it is sort of like practice 00:39:44.000 --> 00:39:49.000 within a conceptually, you know, problem solving oriented 00:39:49.000 --> 00:39:53.000 video. We did all of our studies using pairs as the 00:39:53.000 --> 00:39:57.000 vicarious learners because of 00:39:57.000 --> 00:40:02.000 research by Mickey colleagues that have demonstrated it is 00:40:02.000 --> 00:40:05.000 much more effective to use p airs rather than singles. For 00:40:05.000 --> 00:40:07.000 research sake since this was exploratory work, we wanted to 00:40:07.000 --> 00:40:12.000 get a good trace of what they were saying as they were 00:40:12.000 --> 00:40:14.000 interacting with the videos. Is it better if I stop share 00:40:14.000 --> 00:40:18.000 at this point. » JOE DAUER: Yeah. Yeah. I 00:40:18.000 --> 00:40:18.000 think that is okay. » JOANNE LOBATO, Ph.D.: Okay. 00:40:18.000 --> 00:40:23.000 » JOE DAUER: So another 00:40:23.000 --> 00:40:27.000 question that was earlier on but I think is 00:40:27.000 --> 00:40:29.000 really still pertinent here, the inclusion of faces hamper 00:40:29.000 --> 00:40:33.000 the cognitive process? Meaning like if you were just 00:40:33.000 --> 00:40:38.000 to show the hands and still hear the dialogue, like how 00:40:38.000 --> 00:40:42.000 does the inclusion or exclusion of faces affect how 00:40:42.000 --> 00:40:43.000 the vicarious learning can take place? 00:40:43.000 --> 00:40:46.000 » JOANNE LOBATO, Ph.D.: Wow. 00:40:46.000 --> 00:40:50.000 That's a really -- that's a good question. 00:40:50.000 --> 00:40:53.000 So I have two thoughts. I mean, I don't know the answer 00:40:53.000 --> 00:40:58.000 to that. My thought -- my guess from the work that we 00:40:58.000 --> 00:41:02.000 did on the orientation of vicarious learners towards the 00:41:02.000 --> 00:41:05.000 talent -- again, this was very exploratory -- that the faces 00:41:05.000 --> 00:41:09.000 mattered. You know. The kids wanted to be able to connect 00:41:09.000 --> 00:41:13.000 with and did connect with the talent as peers. You know, I 00:41:13.000 --> 00:41:18.000 sense that the question has to do with cognitive overload. 00:41:18.000 --> 00:41:22.000 And Derrick muller has an interesting paper where he 00:41:22.000 --> 00:41:25.000 tackles head on some research that has been done on 00:41:25.000 --> 00:41:30.000 cognitive overload with the production of v ideos. And he 00:41:30.000 --> 00:41:33.000 says that for dialogic videos, it is actually -- there might 00:41:33.000 --> 00:41:37.000 be some cognitive overload. But on the other hand, the 00:41:37.000 --> 00:41:40.000 importance of getting this conceptions displayed in the 00:41:40.000 --> 00:41:44.000 dialogue is more important. And he showed how that was -- 00:41:44.000 --> 00:41:48.000 I can't remember the exact study right now. But I think 00:41:48.000 --> 00:41:52.000 that there's important things about having the ideas related 00:41:52.000 --> 00:41:55.000 to the individuals in the dialogue. But I think it is 00:41:55.000 --> 00:41:58.000 an open question for investigation. 00:41:58.000 --> 00:42:04.000 » JOE DAUER: Yeah. There was 00:42:04.000 --> 00:42:09.000 a question about why -- and I think you might have hit at 00:42:09.000 --> 00:42:12.000 this at the end. Why learn about parabo las. What is 00:42:12.000 --> 00:42:16.000 motivating -- is there anything in the -- in the way 00:42:16.000 --> 00:42:20.000 that it is presented that is - - is motivating for the 00:42:20.000 --> 00:42:25.000 students in order to learn about the 00:42:25.000 --> 00:42:29.000 p arabolas or is it how to learn how to use the 00:42:29.000 --> 00:42:31.000 definition of the parabola and work through it? 00:42:31.000 --> 00:42:36.000 » JOANNE LOBATO, Ph.D.: That's a good question. In the 00:42:36.000 --> 00:42:40.000 original grant, it was just a small exploratory grant. I 00:42:40.000 --> 00:42:45.000 wanted to pick something -- we did one unit on proportional 00:42:45.000 --> 00:42:49.000 reasoning and one unit on parabola. I wanted something 00:42:49.000 --> 00:42:52.000 that I had experience with working with high school kids 00:42:52.000 --> 00:42:56.000 or undergraduates on. The reason that the topic is 00:42:56.000 --> 00:43:01.000 important, it is something that kids are required 00:43:01.000 --> 00:43:04.000 to cover in high school, especially the vertex form of 00:43:04.000 --> 00:43:09.000 a parabola. It is generally done faster. The reason that 00:43:09.000 --> 00:43:13.000 I wanted to open it up and unpack it, there is a lot of 00:43:13.000 --> 00:43:17.000 opportunity for quantitative reasoning. Really following 00:43:17.000 --> 00:43:20.000 pat Thompson here and talking about attribute that's are 00:43:20.000 --> 00:43:24.000 measurable in a situation. So what I thought -- what I find 00:43:24.000 --> 00:43:28.000 when I work with math majors in a course that I teach where 00:43:28.000 --> 00:43:31.000 I snow these 00:43:31.000 --> 00:43:35.000 -- show these videos, their way of approaching similar 00:43:35.000 --> 00:43:38.000 problems is not to think about -- it seems crazy but not to 00:43:38.000 --> 00:43:42.000 think about points and different things in the plain 00:43:42.000 --> 00:43:45.000 in terms of distances. So that is the quantity that 00:43:45.000 --> 00:43:47.000 seems really important that gets highlighted in Sasha and 00:43:47.000 --> 00:43:50.000 keoni's work and I think that can be really powerful for 00:43:50.000 --> 00:43:52.000 students at both the undergraduate and the high 00:43:52.000 --> 00:43:56.000 school level. 00:43:56.000 --> 00:44:01.000 » JOE DAUER: Yeah. Great. 00:44:01.000 --> 00:44:06.000 There's kind of a series of comments here which I'm going 00:44:06.000 --> 00:44:10.000 to try to synthesize. It was about the interaction with 00:44:10.000 --> 00:44:14.000 Marshall. And so -- watching the video but also his work 00:44:14.000 --> 00:44:18.000 there. And so I'm wondering - - so the question is about 00:44:18.000 --> 00:44:21.000 when he was asked -- when asked what the students in the 00:44:21.000 --> 00:44:25.000 video would do, he kind of has a very different method. 00:44:25.000 --> 00:44:26.000 Right. » JOANNE LOBATO, Ph.D.: Yeah. 00:44:26.000 --> 00:44:30.000 » JOE DAUER: So they're 00:44:30.000 --> 00:44:36.000 wondering if Marshall boulevard he knew more or less 00:44:36.000 --> 00:44:39.000 . And is that what prompted the shift in problem solving. 00:44:39.000 --> 00:44:43.000 Being comparative to those in the video. If that is causing 00:44:43.000 --> 00:44:45.000 the shift in the problem solving that went 00:44:45.000 --> 00:44:50.000 on. » JOANNE LOBATO, Ph.D.: C 00:44:50.000 --> 00:44:53.000 David Walter was my doctoral student at the time. And I 00:44:53.000 --> 00:44:56.000 don't remember all of the details but I do remember that 00:44:56.000 --> 00:45:00.000 Marshall actually looking back on his different solutions 00:45:00.000 --> 00:45:05.000 actually ended up valuing the more quantitative reasoning 00:45:05.000 --> 00:45:08.000 approach that had more explicit intention to 00:45:08.000 --> 00:45:12.000 geometric features and distances in the coordinate 00:45:12.000 --> 00:45:18.000 plain of Sasha and k eoni. » JOE DAUER: Great. And the 00:45:18.000 --> 00:45:20.000 last question really is about the decentering and whether 00:45:20.000 --> 00:45:27.000 like 00:45:27.000 --> 00:45:31.000 -- if you've thought much about if that is a teachable 00:45:31.000 --> 00:45:36.000 skill. Like is that something that instructors -- how do you 00:45:36.000 --> 00:45:37.000 get students to do that decentering a little more 00:45:37.000 --> 00:45:42.000 effectively. » JOANNE LOBATO, Ph.D.: Yeah. 00:45:42.000 --> 00:45:46.000 You know, we've been -- in math ed for teacher 00:45:46.000 --> 00:45:50.000 preparation, we've been sharing videos of kids 00:45:50.000 --> 00:45:55.000 thinking for, you k now, two decades now. But one thing 00:45:55.000 --> 00:45:58.000 that I think is really special about videos where you can 00:45:58.000 --> 00:46:02.000 track the same pair of students over time -- by the 00:46:02.000 --> 00:46:05.000 way, I've been using the parabola unit in a math course 00:46:05.000 --> 00:46:08.000 that I teach at San Diego State for perspective 00:46:08.000 --> 00:46:14.000 secondary high school teachers . They're right at the end of 00:46:14.000 --> 00:46:19.000 their math major. And I notice that they are able to 00:46:19.000 --> 00:46:23.000 decenter in part because they come to know those kids. It 00:46:23.000 --> 00:46:28.000 is not just quick excerpts but they actually start to become 00:46:28.000 --> 00:46:31.000 able to think like the kids. And we're actually using some 00:46:31.000 --> 00:46:34.000 of these 00:46:34.000 --> 00:46:39.000 materials at 00:46:39.000 --> 00:46:44.000 CSU channel islands. I think this projectory of the 00:46:44.000 --> 00:46:47.000 students being able to have sustained experience with the 00:46:47.000 --> 00:46:52.000 same students over time helps with that decentering. That 00:46:52.000 --> 00:46:56.000 they come to actually value and be able to predict this -- 00:46:56.000 --> 00:47:00.000 what the students will do and come to see them as really 00:47:00.000 --> 00:47:03.000 capable problem solvers. And I think that longer exposure 00:47:03.000 --> 00:47:05.000 has a special affordance that I would like to do more 00:47:05.000 --> 00:47:07.000 research on. 00:47:07.000 --> 00:47:11.000 » JOE DAUER: Great. Well, so 00:47:11.000 --> 00:47:15.000 that's the end of the time that we have. And so thank 00:47:15.000 --> 00:47:19.000 you very m uch, Dr. Lobato, for that wonderful 00:47:19.000 --> 00:47:24.000 presentation. We really appreciate that. Hopefully 00:47:24.000 --> 00:47:26.000 you're able to still be at the conference so the rest of the 00:47:26.000 --> 00:47:31.000 people can track you down if they have additional questions 00:47:31.000 --> 00:47:36.000 or e-mail you. So we have a short b reak. There's about a 00:47:36.000 --> 00:47:40.000 15-minute break. And then we will get back together at 2:30 00:47:40.000 --> 00:47:45.000 . Those are the concurrent sessions in rooms B, C and D. 00:47:45.000 --> 00:47:47.000 All right. So thank you all. And we will see you in the