In addition to the questions we are answering, I added a question that occured to me after attending Paul Kirschner's lecture titled "What do we need to keep in mind when confronted with mega trends that challenge education?" in the international work shop at University of Oulu. the question is: Is it a hype or a trend?
Regulation of Learning
March 27th, 2018
Individual Paper 1
Malmberg, J. (2018, March). Are we together or not? Sequential interplay of monitoring and physiological synchrony during a collaborative exam. Paper session presented at the LET2018 Conference, Oulu
The aim of this study is to explore whether individuals are in synchrony when working on the same task. In addition to how they are synchronizing during this task especially if their interaction is not verbal nor observable. With a specific focus on understanding the process of monitoring in the context of collaborative learning.
As for the research questions, there were two research questions. The first one was, what do physiological signals indicate about individual students’ monitoring processes? Secondly, how does physiological synchrony and its interplay with monitoring connected in a collaborative exam situation?
Participants were twelve high school students, in four groups of three students each, aged 15 to 16 years. These students were in an Advanced physics course. They were monitored in a collaborative exam (28 minutes and 55 seconds (Std = 53s). Data collection method were video observations by 360-degree camera and Electro Dermal Activity (EDA).
The results revealed that there was no joint monitoring by all the students in every phase of the learning process. Also, the EDA peeks had reflected monitoring activity. However, there was a vague link between physiological synchrony and sequential interplay of monitoring. Finally, monitoring does not reveal about “sharedness”, but more about “active mind” which was shown in this study (Järvela, Hadwin, Malmberg & Miller, 2017)
To me I find it too difficult to uncover the synchronicity of the students' non verbal interaction. Even if there were some signs that seemed related or connected but as long as they are not expressed verbally we can't garantee or make sure that it is synchronicity. Unless telepathy gadgets started to be in the market. If we are able to read each others' mind directly then it would be easy to find synchronicity.
Is it a hype or a trend?
To me this is just a hype that would fade away after couple of years later, since the connection between monitoring or any aspect of seelf-regulation and physiological synchrony was found vague and weak. The more evidence and connection we can get the stronger are the results and this is not the case here. And since it is non verbal and inside the students brain, no one can get a concrete evidence.
Individual Paper 2
Dindar, M. (2018, March). Interplay of temporal changes in self-regulation, academic success and physiological synchrony. Paper session presented at the LET2018 Conference, Oulu.
This study aimed at investigating the chronological changes of self-regulated learning processes during collaborative learning and their behavioral, motivational and emotional regulation and academic achievement. Second, the relationship between Physiological Synchrony (PS) of students and their self-reports about between cognitive, behavioral, motivational and emotional change during learning sessions and finally, the relationship between physiological synchrony of students and academic accomplishment.
The participants were 31 high school students in an advanced physics course. There was an overrepresentation of females over males in this study, with twenty-three females and only eight males. As for the collaborative online environment, it was EdX platform and it was used to instruct the participants in the collaborative tasks.
While the data collection was divided into two parts, the first one included six groups and self-reports were collected from them. Whereas the second part included four groups and not only self-reports were collected from them but also Electro Dermal Activity (EDA).
neither motivational change nor emotional change.
I will represent the results of this study based on the same sequence of the research questions to avoid the repetition of the questions. First, the researchers have found a relation between the behavioral change and cognitive change are highly related. According to him, the reason behind this relation is that in order to act properly your cognition should be in line with your behaviors and actions. Also, the behavioral change was related to the motivational change. As for the cognitive change, there was no direct relationship neither with motivational change nor emotional change.
To me, I find it very interesting to run such a study but not on a purely cognitive task, but on a task that requires a lot of socio-emotional regulation. Such environment can be found in Education and Globalization master degree. The courses in this major and the diversity of nationalities with different backgrounds in it make a good grounding for socio-emotional conflicts in a collaborative task. the different background and different believes of the student combined with sensitive issues, would create socio-emotional conflicts that the students need to regulate themselves strategically in order to be able to achieve the goal.
Individual Paper 3
Järvenoja, H. (2018, March). Measuring motivation and emotion regulation on-line. Paper session presented at the LET2018 Conference, Oulu.
In her presentation, Hanna presented their interest in studying motivation and emotion regulation in real-time situations and that they used Ionline, process-oriented approach. In an attempt to understand better how motivation emotion regulation is actually taking place as a part of learning process. By In her presentation, Hanna presented their interest in studying motivation and emotion regulation in real-time situations and that they used online,better understanding of these complex aspects, they will be able to support learners to improve their regulation in their own learning and provide them with tools that help in coping and maintaining their wellbeing during the learning processes.
Collins (2009) discussed the relation between motivation and self-regulation in her review of Schunk and Zimmerman’s book “Motivation and Self-Regulated Learning: Theory, Research, and Applications”. They defined self-regulation as “controlling one’s own conduct in order to achieve a goal.” p.476. They also stated that motivation can be a precursor to self-regulated learning (2009, p.276) and it can influence its processes.
The researcher highlighted the fact that motivation is not static but it is a constant process of maintaining, building, adapting and directing the motivation within a situation, not to forget the emotional reactions that are simultaneously occurring too. All these features and multifaceted layers of motivation and emotion cannot be grasped using one type of measure, that is why they are using online, process oriented approach.
She also discussed four principles that they took as basic assumptions. First principle is that motivation is situation and content specific, which means that in order to understand motivation in real life, the need to study it in natural learning settings with real learning tasks was a must. Second, motivation in learning is both individual and social, for example the AIRE questionnaire (Järvenoja, Volet & Järvelä, 2013) was done individually but it was interpreted and presented on both individual and group level. Third, effects of motivation and emotions in learning are multilayered and we need to have multiple methods to grasp those layers and depending on what layer the researcher are going to focus, also they need to decide which tool is suitable for measuring it and how to combine these layers to get a comprehensive understanding of these processes. She gave examples about using untraditional methods like processing data from multiple sources like physiological data, eye tracking, log file data in order to measure multilayer motivation and traditional ways of gathering data like video data and using stimulated recall interview and retrospective interview and find subjective interpretations of students of those situations that are taking place. Finally, motivation and emotion regulation matters in successful learning. Emotional reaction in relation to cognitive processes going on in a video data.
Motivation is a pillar in learning and education. it has an essenial and crucial role in enhancing the learning process. the more researchers about it the more we know about it and about its impact and how we can get advantage of it.
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References
Collins, N. (2009). Motivation and Self-Regulated Learning: Theory, Research, and Applications. The Journal of Higher Education, 80(4), pp. 476-479.
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Järvenoja, H., Volet, S., & Järvelä, S. (2013). Regulation of emotions in socially challenging learning situations: An instrument to measure the adaptive and social nature of the regulation process. Educational Psychology, 33(1), 31-58.
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Miller, M., Järvelä, S., & Hadwin, A. (2017). Self-regulation, co-regulation, and shared regulation in collaborative learning environments. In Handbook of self-regulation of learning and performance (pp. 99-122). Routledge.
Paper session 2
March 29th, 2018
Individual Paper 1
Sobocinski, M. (2018, March). Exploring small-scale adaptation in socially shared regulation of learnin. Poster session presented at the LET2018 Conference, Oulu
The researcher had started with defining regulation. Panadero (2017) stated that “Self-regulated learning (SRL) is a core conceptual framework to understand the cognitive, motivational, and emotional aspects of learning.” p.1.
She stated that regulation unfolds cyclically and recursively over time, in the last phase what the students reflect on, the conclusions that they make they will use in the next planning phase. She also defined adaptation, which is a key process of socially shared regulated learning and self- regulated learning. It is the process of updating the beliefs and knowledge set in the previous phase.
Then she stated that the need for regulation is recognized through metacognitive monitoring. Which was defined by Winne and Perry (2000) as “the gateway to self-regulating one’s learning”. p. 540. When we are monitoring we will be able to identify and be aware if we are facing a challenge and that we should start to strategically adapt a strategy.
The aim of Marta’s study was to investigate how metacognitive monitoring happens and how it is related to small-scale adaptation during collaborative learning, using multimodal data. The study’s research questions aimed at a) identifying the type of monitoring the students use, b) how does the adaptation that happens on the fly happen during collaborative learning, c) identifying the relationship between monitoring, adaptation and physiological synchrony.
There were twelve high school students as participants in an advanced physics course. There were eighteen learning sessions and six collaborative sessions lasted for 75 minutes (these were the one analyzed later). The data collection methods were Empatica S3 sensors to measure heart rate, and video data to collect the students’ discussions, gestures and reactions.
Coding the video data is very important and finding the right nodes is crucial in order to have a data that answers your research questions. What the researcher has done in her coding was precise and straightforward and that led to clear results.
Results showed that the most frequent events were monitoring behavior in task enactment phase, then comes monitoring cognition in the same phase. Later, definition phase comes were monitoring behavior and then cognition comes respectively. Also, it was noticed that monitoring cognition was most likely to be followed by monitoring behavior, whereas monitoring motivation and emotion were rarely followed by any reaction from the group.
Individual Paper 2
Haataja, E. (2018, March). Monitoring in collaborative learning and physiological synchrony – How they co-occur? Poster session presented at the LET2018 Conference in University of Oulu, Oulu.
The aim of the study was to find connections between monitoring and temporal changes in physiological synchrony. The setting of the study was high school students and their task was the same as Marta’s study since they are in the same project. WeSPOT was used as an environment, this environment differs than EdX environment, it has been developed for inquiry- based learning. Data collection methods were video data and EDA signals. Dowson, Schell & Filion (2017) defined EDA as “ a sensitive peripheral index of sympathetic nervous system activity that has proven to be a useful psychophysiological tool with wide applicability” p.176. Three groups were analyzed thoroughly, because they had the most accurately physiological data.
The study had three research questions, first, how do students monitor their cognitive, affective and behavioral processes? Second, do students physiologically synchronize during collaborative learning? And third, how monitoring co-occurs with physiological synchrony?
As for the results, his results were in line with Marta’s results; that students were monitoring cognition and behavior, while monitoring emotion and motivation was not that frequent. Also, he confirmed that there physiological synchronity between group members in collaborative learning. As for how monitoring is co-occurring with physiological synchrony, there is potentiality that physiological synchrony might reveal conditions of joint learning.
Individual Paper 3
Pijeira Diaz, H. (2018, March). Investigating collaborative learning success with physiological coupling indices based on electrodermal activity. Paper session presented at the LET2018 Conference in University of Oulu, Oulu.
The aim of this study is to compare five different Physiological Coupling Indices (PCIs) (physiological synchrony) that the researcher found in literature, in order to find out which one is mostly related to three different aspects of collaborative learning. These aspects are Collaborative Will (CW), Collaborative Learning product (CLP) and Dual learning gain (DLG) and that is the mean of the difference between the pre and post-tests.
Hence, the researcher can enrich the design of digital feedback tools that use learning analytics through physiological data. These five are a) Signal Matching (SM) which refer to the process of comparing of two antidotes of two individuals, b) Instantaneous Derivative Matching (IDM), c) Directional agreement (DA) (Elkins et al., 2009) , d) Pearson’s correlation coefficient (PCC) (Henning, Boucsein & Gil, 2001), e) Fisher’sz -transform (FZT) (Chanel et al., 2013).PCI
There were 48 high school participants, 27 females and 21 males. Their age ranged between 16 and 19 years old. The experiment occurred in the LeaForum and the task is the same as Marta’s and Eetu’s. As for the data collection methods there were four different types, first, the researcher used MSLQ questionnaire which is “is a self-report instrument designed to assess college students' motivational orientations and their use of different learning strategies for a college course” (Pintrich, 1991, p.3). method was pre- and Secondpost- tests, the third was group’s report and finally 6 Empatica S3 were used.
Later, there was the data processing phase, the data passed through several steps before reaching the PCI calculation and correlation part. The results showed that there was no correlation between SM, PCC and FZT and any of the collaborative aspects that was mentioned earlier. Yet, in terms of collaborative will and collaborative product, IDM showed a moderate correlation with them but not with DLG. Finally, there was a strong correlation between DA and DLG.
Is it a hype or a trend?
According to Kirschner (2018) Learning Analytics is now at its peak of inflated expectations and that it is an educational hype, that will fade soon. I can't be with or against him since I don't have a strong background about this subject. But I know that upcoming years will show us the real answer.
References
Elkins, A. N,. Muth, E. R., Hoover, A. W., Walker, A. D., Carpenter, T. L, and Switzer, F. S. (2009). Physiological compliance and team performance. Applied ergonomics, 40(6), 997-1003. doi:10.1016/j.apergo.2009.02.002.
Chanel, G., Bétrancourt, M., Pun, T., Cereghetti, D., & Molinari, G. (2013). Assessment of computer-supported collaborative processes using interpersonal physiological and eye-movement coupling. In Affective Computing and Intelligent Interaction (ACII), 2013 Humaine Association Conference on (pp. 116-122). IEEE.
Dawson, M. E., Schell, A. M., & Filion, D. L. (2017). The Electrodermal System. In J. T. Cacioppo, L. G. Tassinary, & G. G. Berntson (Eds.), Handbook of Psychophysiology (pp. 217–243). Cambridge: Cambridge University Press. Retrieved from http://doi.org/10.1017/9781107415782.010
Henning, R. A., Boucsein, W. Claudia Gil, M. (2001). Social-physiological compliance as a determinant of team performance. International Journal of Psychophysiology, 40(3), 221-232. doi:10.1016/S0167-8760(00)00190-2.
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Kirschner, P. A. (2018).What do we need to keep in mind when confronted with mega trends that challenge education?. Paper session presented at Global Challenges and Education: Seeking for Solutions at university of Oulu, Oulu.
Panadero, E. (2017). A Review of Self-Regulated Learning: Six Models and Four Directions for Research. Frontiers in Psychology, 8, 422. doi: 10.3389/fpsyg.2017.00422.
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Pintrich, P. R. (1991). A manual for the use of the Motivated Strategies for Learning Questionnaire (MSLQ).
Winne, P. H., and Perry, N. E. (2000). “Measuring self-regulated learning,” in Handbook of Self-Regulation, eds M. Boekaerts, P. R. Pintrich, and M. Zeidner (Orlando, FL: Academic Press), 531–566.
Paper session 3
April 10th, 2018
Individual Paper 1
Törmänen, T. (2018, April). Exploring collaborative groups’ emotional states with video and physiological data. Paper session presented at the LET2018 Conference in University of Oulu, Oulu.
Tiina’s research is part of Em-Reg project. Her study is aiming to track the role of socially shared emotion regulation for collaborative learning progress. It is exploring the role of emotion regulation for collaborative progress and the reciprocal relationship between individual students’ affective states and emotion regulation within groups.
The researcher will follow multiple process-oriented data sources that bring resourceful information from authentic situations. She introduced academic emotions, this term was first introduced by Perkun, later he developed a questionnaire to measure the nine achievement emotions that students experience in academic settings. This questionnaire is called “The Achievement Emotions Questionnaire (AEQ)” (Perkun, Goetz, Frenzel, Barchfeld & Perry, 2011). She also stated that according to Perkun (2016), there are two dimensions of affective states and they are valence and activation. She will use EDA to measure the physiological arousal of the students.
The research questions are three, first, how is the emotional state of collaborative groups vary in terms of observed valence and activation a collaborative learning session ? Second, is there a concordance between groups’ observed emotional activation level and physiological activation level measured with EDA? And finally, in what kind of situations is group members’ physiological activation level in synchrony?
As for participants, there were 41 students divided into twelve groups. Their task was to design and construct a model of house that is highly efficient and use solar energy. The study was performed in LeaForum.
The researcher concluded that in one learning session, the emotional state of a group might vary a lot. In addition, it was activating more than de-activating and this activation was often negative. The amount of socio-emotional expressions and valence and the activation of socio- emotional segments were different among the groups.
Collecting physiological data can be benefecial for learning sciences yet it needs a good grounding and finding a strong linkage with the learning process would reveal and uncover a lot of mysteries and help in enriching the literature review.
Individual Paper 2
Siklander, Kangas, Randolph, & Ruokamo (2017). Poster presented at Earli 2017 Conference, Finland, Tampere.
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Finally playful learning is here. This kind of topic and research is what I like the most. I feel that playfulness is needed in every person life and if it is missing, there should be some methods or interventional steps that would help in returning such an essential feature to our lives.
The aim of the study was to see how educators see their own playfulness. As it appears from the title, the participants are different types of educators and teachers, whether students or retired or at the moment working as educators or teachers. They were 123 participants, where women was the majority with 107 women involved and their age ranged between mid sixties and early twenties. The data collection method was a questionnaire named Staempfli’s (2005, 2007) Adult playfulness Scale (APS) (Finnish version). They followed multivariate analysis to examine the influence of gender and age on the adults’ playfulness subscales.
As for the research questions, they are three. First, how do adult educators evaluate their own playfulness? The results revealed that participants assess themselves as quite or extremely playful. Also, highly playful adults are challenged with mysteries and unsolved problems and find it stimulating to be original in their thinking and behavior. Second, what are the most general qualities of playfulness among educators? Here the results showed the sentences were related to social, cognitive, creativity and imagination and embodiment aspects. Finally, are there variations in experienced playfulness among educators of different ages and gender? Here, the researchers found that there are no differences in perception of playfulness among educators between 20 to 64 years old. Interestingly, it showed that male educators are slightly less playful than female educators.
I would be very interested in running this APS questionnaire on men and women before and after marriage, also on mothers before giving birth and after giving birth. Then compare the results to see if they are the same or how much will they differ. Because I feel that there will be significant difference in the answers of the participants even if it is the same questionnaire, due to the major changes and responsibilities that happens in these critical changes in life
References
Pekrun, R., Goetz, T., Frenzel, A. C., Barchfeld, P., & Perry, R. P. (2011). Measuring emotions in students’ learning and performance: The Achievement Emotions Questionnaire (AEQ). Contemporary educational psychology, 36(1), 36-48.
Pekrun, R., Goetz, T., Titz, W., & Perry, R. P. (2002). Academic Emotions in Students’ Self-Regulated Learning and Achievement: A Program of Qualitative and Quantitative Research. Educational Psychologist, 37(2), 91–106. https://doi.org/10.1207/S15326985EP3702.
Pekrun, R. (2016). Academic Emotions. In K. R. Wentzel& D. B. Miele(Eds.), Handbook of motivation at school(2nd ed., pp. 120–144). New York, NY: Routledge
Staempfli, M. B. (2005). Adolescent playfulness, leisure and well-being.
Staempfli, M. B. (2007). Adolescent playfulness, stress perception, coping and well being. Journal of Leisure Research, 39(3), 393-412.
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Siklander, Kangas, Randolph, & Ruokamo (2017). Poster presented at Earli 2017 Conference, Finland, Tampere.
Paper session 4
April 12th, 2018
Individual Paper 1
Mykkänen, A (2018, April). Students’ interpretations of a group awareness tool in a collaborative learning setting. Paper session presented at the LET2018 Conference in University of Oulu, Oulu.
I thought collaboration was a smooth process that happens naturally and the desired results would come as a normal consequence. But it turned out that collaboration does not necessarily mean that everything is going to be well and smooth with no obstacles or socio-emotional conflicts. this is what happened to me and according to the researcher this might be due to insufficient regulation, unequal participation and miscommunication between the group members (Mykkännen, 2018).
The researcher was talking about tools that can be used to raise the awareness of the group in collaborative learning about different aspects and possible dysfunctionalities of their collaboration and help them in visualizing their participation, and this would help the group in giving feedback to each member in the group and make groundings for evaluation.
He then introduced different aspects of group awareness tools like, tools that can inform the group members about others’ participation in the joint task (Janssen et al. 2011) such tool can help in identifying the free riders in the group, where Bartlett (1995) defined those free riders as “students who do not participate to the best of their abilities.” p.131. Another awareness tool can prompt the progress of collaboration and socially shared regulation, also there is a tool that raises the awareness of the cognitive aspects of group performance (Kim & Ryu, 2013) and finally a tool that offers support to group members by offering peer feedback and reflection within the group.
The aim of the study was to identify what type of advantages and disadvantages do students describe group awareness tool usage after a series of collaborative tasks.
The participants in this study were 44 second-year teacher education students in a math didactics course with a duration of seven weeks. The study was divided into two parts, the first one is teacher-led sessions whereas the second on is student-led collaborative tasks. At the end they were semi-structured interviews that lasted between 15 to 25 minutes. And the group awareness tool that was used in this study is S-Reg tool.
The results were divided into three main categories, the positive interpretations, the negative interpretations and needs improvement. The positive interpretations were many, like "the tool helps to understand own and group members’ state of mind and prompts discussion". The negative interpretations, were like "it has no benefits on the group members or it increased frustration". Finally, for the need improvement category, the timing of the tool usage should be adjusted.
After reading about different aspects that awareness tools have and was thinking if there is a tool that can collect the aforementioned aspects together in one tool, that way it will give richer data and raise the awareness in a better and quicker way.
Also, the feature of prompts that raise the awareness, was previously handled in socially shared regulated learning course when we designed an environment that can help the students in raising their awareness about collaboration and help them in socially regulating their learning. In my group, we choose Edmodo were we defined in details the different features that already exist in it and helps in regulation and highlighted the features that can be added in order to improve the regulating of learning within the group. Finding the practical tool that would help a lot in understanding self-regulated learning.
Is it a hype or a trend?
To me I see it as an educational trend, that is neccessary and would help a lot in revealing a lot of missing details that might help in creating the whole picture of self-regulated learning and its aspects in the learning process.
Individual Paper 2
Kurki, K. (2018, April). Exploring regulatory interactions among young children and their teachers – focus on teachers’ monitoring. Paper session presented at the LET2018 Conference in University of Oulu, Oulu.
According to Eisenberg (2010) emotions related to self-regulation progresses rapidly in the early years of life and this progress becomes slower in adulthood. That shows the importance of the researches that are investigating emotions, behavior and self-regulation in early childhood.
First, when I heard about the regulation of emotion and behavior among children, I was surprised how such a sensitive complicated issue can be dealt with among children. But then I actually found that it is very logical to study it among children since children are so emotional at this stage and sometimes do not know how to express their needs or feelings in the appropriate way. Hence the teachers in the kindergarten play an essential role in helping those kids in dealing with their own emotions and in expressing them.
The study aimed at investigating the types of emotion and behavior regulation strategy that children use independently or with teacher support. Also, it aimed at identifying how teachers’ level of monitoring contributes to children’s strategy use. There were 30 children and 8 teachers as participants. The study settings were open day-care facilities designed for research purposes. Videos of authentic open day-care interaction where the data that was collected. The videos were coded and analysed.
Research questions and results:
RQ1: what kind of regulation strategy types do children use independently or with teacher support?
For the independent strategies, the most significant one that was used by the children was situation modification, then comes response modulation where the difference between them is slight. Later comes providing information as the third strategy. As for the teacher supported strategies, redirecting activity was the most prominent one where it represented more than 60 % of the whole strategies used.
RQ2: how the teachers’ level of monitoring in the challenging situation related to children’s different strategy types?
The researcher found no significant difference between the active and no/weak monitoring in terms of children’s types of strategies.
I found it very interesting to investigate in this open day-care facility that was designed for research purpose, how the children are adapting their eating habits after a positive feedback or a negative one. Because this is what happens with my children, after I make a propaganda or a dramatic scene with my husband of how this type of food is very delicious and tasty but not directing the discussion to them, and they start eating they start to talk positively about the food even if they didn’t like it previously and they finish their plate. But when they hear some negative comment from me or my husband towards certain type of food or even just a gesture, they start to nag about how bad is this food and they don’t finish their plate. I really want to study this phenomenon, also see how this can be applied not only to food habits but on other behavior too. Regulating emotion and behavior is essential for kids and the teachers play a vital role
Individual Paper 3
Siklander, P. (2018, April). Nature as a setting and resource to promote learners’ agency and competences in education. Paper session presented at the LET2018 Conference in University of Oulu, Oulu
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This diagram shows the different aspects that educational environment can be developed with. I really liked it.
This is a current study that needs another round of results’ analysis. The researcher introduced the importance of nature and how it can provide many different experiences for the learners. Then she introduced the term agency, which is a term that we have discussed it previously in our self-regulated learning course. According to Engle and Conant (2002) Student Agency is considered a social action that emerges in relation to associating with other people. While Efficacious Agency is the combination of resilience, self-regulation and self- efficacy (Hyvönen et al., 2014)
The aim of this research is to investigate how nature, specifically a hiking course in Finnish wilderness would allow students to exercise their agency and how it promotes their competences. As for the research questions, they were two. The first one is in which ways students’ agency emerges during a hiking course?, while the second one is how the competences needed in the activities are manifested?
The methodology followed was qualitative inductive content analysis (Schreier, 2012). This analysis produced four categories of students’ agency: responsibility, resiliency, collaboration and feeling of success; this was an answer for the first question. As for the second question, the hiking course it provided the students with opportunities to exercise problem solving, social and negotiation skills and personal and social responsibility in a collaborative way. The results have shown that nature provides rich environment for practicing competences and exercising agency.
I would really like the idea of having such a course in our master program were we can really practice collaboration and regulation of emotions in a unique way that can not be forgotten. The linkage between human and nature should be empowered in this digital era and specially for young learners, who are emmersed in technology in their everyday life and that would harm their brain development and kills creativity.
References
Eisenberg, N. (2010). Emotion-Related Self-Regulation and Its Relation to Children's Maladjustment. Annual Review of Clinical Psychology, 6, pp. 495-525.
Engle, R. A., & Conant, F. R. (2002). Guiding principles for fostering productive disciplinary engagement: Explaining an emergent argument in a community of learners classroom. Cognition and Instruction, 20(4), 399-483.
Hyvönen, P., Kronqvist, E. L., Järvelä, S., Määttä, E., Mykkänen, A., & Kurki, K. (2014). Interactive and Child-Centred Research Methods for Investigating Efficacious Agency of Children. Varhaiskasvatuksen Tiedelehti Journal of Early Childhood Education Research, 3(1), 82-107.
Janssen, J., Erkens, G., & Kirschner, P. A. (2011). Group awareness tools: It’s what you do with it that matters. Computers in Human Behavior, 27(3), 1046-1058. doi:10.1016/j.chb.2010.06.002.
Kim, M., & Ryu, J. (2013). The development and implementation of a web-based formative peer assessment system for enhancing students’ metacognitive awareness and performance in ill-structured tasks. Educational Technology Research and Development, 61(4), 549-561. doi:10.1007/s11423-012-9266-1
Schreier, M. (2012). Qualitative content analysis in practice. Sage Publications.
Keynote
April 24th, 2018
Järvelä, S (2018, April). Multimodal data to understand students’ cognition, metacognition, motivation and emotions in a learning process.
This keynote was the final lecture we had in this course, where the researcher had presented some projects that are happening at LET department at University of Oulu. It summed most of the research trends that we had earlier. However, I find it more enlightening to me if it was the first lecture we had. It would have given an excellent introduction for all the lectures that comes after it.
The researcher introduced the learning process and how it is a complex process. Then she talked about SRL theory and how it helps in understanding the complex process of learning. Later she introduced the elements that help in making collaboration successful. Then, she mentioned two studies that big data was collected from them and these are what we had in previous lectures (preparing a breakfast for an athlete and advanced physics course). Multimodal data collection methods were applied like EDA and heart rate, 360-degree video capture and audio, EdX log data and Mobile eye tracking. This multimodal data collection would provide subjective and objective data markers, complement with different data channels, new means for data triangulation, capture the temporal and cyclical processes and finally capture critical phases of the SRL, CoRL and SSRL processes. In addition to multimodal data collection, Learning Analytics is also needed. With the combination of both, bigger data will be analyzed leading to stronger evidence.
What was more interesting is when the researcher talked about Artificial Intelligence AI. AI might offer a great aid in the future in understanding learning processes with all its complexity.
I loved this quotation a lot, it was on the final slide in the researcher powerpoint presentation.
