Inquiry Based Learning

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Does artificial tutoring foster inquiry based learning?

Does artificial tutoring foster inquiry based learning?

ABSTRACT: This contribution looks at the Intelligent Tutoring Interface for Technology Enhanced Learning, which integrates multistage-learning and inquiry-based learning in an adaptive e-learning system. Based on a common pedagogical ontology, adaptive e-learning systems can be enabled to recommend learning objects and activities, which follow inquiry-based learning (IBL) and multistage learning (MSL) pathways. This paper will show how learning activities and pathways are formalized so that they become suitable for artificial tutoring. Therefore relations between different IBL & MSL learning objects are establish as learning pathways, in a way that they become readable to e-learning systems. Developing specifications for pedagogical meta-data and pedagogical rules derived from learning pathways provide the opportunity to connect technology enhanced learning with IBL & MSL. The reader will learn how the complex structure of inquiry-based learning and multistage learning was adopted to the extent that it can be facilitated by adaptive e-learning systems. Results show that the transition from IBL to computational IBL requires a certain adaption of the student-centred notion to become feasible for computational formalities.
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Self-Generation in the Context of Inquiry-Based Learning

Self-Generation in the Context of Inquiry-Based Learning

Multiple learner characteristics, such as need for cognition, cognitive abilities, and prior knowledge, have an influence on self-generation in inquiry-based learning. Need for cognition (NFC) is a learner’s tendency to engage in and enjoy effortful cognitive endeavors ( Cacioppo and Petty, 1982 ) and has an influence on whether or not a deeper learning strategy like self- generation is applied. A number of studies have demonstrated that NFC plays a distinctive role in active information processing as a descriptor and predictor, over and above cognitive abilities (e.g., Cacioppo et al., 1996 ; Cohonner and Mayer, 2018 ). Recent findings revealed that more than 50% of the variance in performance (success in self-generation) during the inquiry task could be explained by NFC and another important factor – cognitive abilities [measured by school type 1 (Kaiser and Mayer, unpublished)]. The latter represent one determinant of an individual’s learning capacity in the sense of the Berlin Model of Intelligence ( Jäger, 1984 ). Pattern recognition and inductive thinking constitute a necessary basis for all scientific inquiry 2 ( Kuhn et al., 1988 ). They are special abilities referring not only to detecting patterns, resemblances, or other kinds of regularities, but also applying simple logic in order to predict what will happen next.
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Effects and Prerequisites of Self-Generation in Inquiry-Based Learning

Effects and Prerequisites of Self-Generation in Inquiry-Based Learning

The lack of a positive generation effect in the long run—that we expected to find between GF and RR according to previous laboratory results—can be explained by the unique features of the inquiry-based learning environment, the complexity of the learning content, and learners’ characteristics (see Introduction). By using inquiry-based learning, which is a collaborative form of learning, it could not be guaranteed that all students would successfully generate all information completely independently and unaffected. Communication among students with different learning characteristics (e.g., cognitive abilities, prior knowledge) through collaborative learning, which is common in everyday instructional practice, led to interaction and the exchange of information among students. However, in the end, own performance and therefore a high degree of activity is precisely a distinctive prerequisite for the generation effect. As long as information could not be generated due to missing preexisting schemata, it could not be remembered [ 27 ]. Additionally, even though we tried to implement this requirement by using individual work phases, feedback, and a computer-based introduction into the material, there were still students who failed to generate their own hypotheses and interpretations.
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Inquiry-based learning put to test: Long-term effects of the Swedish science and technology for children program

Inquiry-based learning put to test: Long-term effects of the Swedish science and technology for children program

The purpose with this paper is to make a contribution with respect to the empirical strand of this literature. While our analysis concerns Sweden we believe it to be of general interest. To begin with, the science and technology for children (STC) program that we study is a very international phenomenon. Originally developed in the U.S., different versions of the program today exists in a number of countries like, e.g., Chile, Thailand, China and Germany, as well as in Sweden. And, to the best of our knowledge, there is no previous large scale assessment of the effects of the STC. Undoubtedly, this is to a large extent due to a lack of appropriate and reliable outcome measures. This shortcoming is not limited to assessments of inquiry-based learning provided through the STC. Geier et al. (2008, p. 924) note: “The lack of student-level distal standardized test data to demonstrate achievement gains from standards-based inquiry science curricula remains a weakness in the literature.”, distal tests referring to statewide standardized tests, as opposed to local test [Geier et al. (op.cit., p. 923)].
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A kutatásalapú tanulás/tanítás (’inquiry-based learning/teaching’, IBL) és a természettudományok tanítása

A kutatásalapú tanulás/tanítás (’inquiry-based learning/teaching’, IBL) és a természettudományok tanítása

A tanulmány célja, hogy bemutassa az IBL módszer sajátosságait, alkalmazásának fontosságát, előnyeit és lehetőségeit. A tanulmány első része leírja, milyen nyelvi prob- lémákat, kérdéseket vet föl az ’inquiry-based learning/teaching’ (IBL) fogalom alkalma- zása a magyar szakirodalomban: mennyire zavaró a szó szerinti fordítás, hogyan közelít- hető tartalma a magyar nyelvhez; milyen szinonim vagy rokon kifejezések, koncepciók kapcsolódnak hozzá; milyen hagyományaik vannak ezeknek iskolai gyakorlatunkban. Ezt követően a külföldi szakirodalom alapján sor kerül a kutatásalapú tanulás/tanítás módszer értelmezésére, megkülönböztető jegyeinek leírására, a tradicionális tanulással és más induktív megközelítésű módszerekkel való összehasonlítására, továbbá alkalma- zása fontosságának és előnyeinek ismertetésére, az alkalmazásával kapcsolatos kritikai észrevételek és a gyakorlatba való beépítési lehetőségek bemutatására. Az utolsó rész a módszer hazai bevezetésének indokaira és lehetőségeire fókuszál.
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Working with teachers on inquiry based learning (IBL) and mathematics and science tasks

Working with teachers on inquiry based learning (IBL) and mathematics and science tasks

Inquiry-based learning (IBL) and analysis of ‘appropriate’ mathematics and science tasks were the focus of this professional development programme, as these are said to increase students’ interest of and attainment levels in mathematics and science education. The data are anchored in observations and feedback/evaluations from a two-day session with a selected group of teachers, where the focus was on mathematics and science task analysis, in order to develop an awareness and knowledge of characteristics of mathematics and science tasks. Results show that during the event teachers developed a deeper understanding of task characteristics, of constraints and affordances of particular IBL tasks; and they reasoned more critically with respect to particular features and selected tasks more carefully. This, it is argued, lies at the heart of productive professional development and the enhancement of teacher knowledge in and for teaching.
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Inquiry based learning: why buying a car with a tree included? Enhancing science and mathematic learning

Inquiry based learning: why buying a car with a tree included? Enhancing science and mathematic learning

Transmission-based pedagogies where students are considered as passive receivers and reproducers of information do not support the development of skills and competences. Society is currently demanding critical thinkers, able to efficiently select and use information, solve problems, adapt to new situations and keep on learning in an increasingly complex and rapidly evolving society. Therefore, there is an urgent need to support those teaching approaches which foster students’ active learning in science and mathematics, and which promote not only conceptual understanding of key curricular topics, but also the acquisition of skills and competences.
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Development of questioning in inquiry-based pedagogy. Pilot study

Development of questioning in inquiry-based pedagogy. Pilot study

Mathematics education in Slovakia goes through several changes that are driven from inner but also from outside needs. International comparative studies are one of the main outside factors. For example, an international comparative study OECD PISA 2003 was focused on mathematical literacy and Slovakia was not significantly different from the OECD average. From that time Slovak mathematics performance has not significantly changed (Koršňáková et al., 2009). On the other hand, the biggest inside change was the school reform in 2008. This reform offers more freedom for schools in preparing their school educational programme. This possibility enables the usage of innovative methods, such as Inquiry-Based Learning (IBL). For teachers, these are often new approaches and, therefore, a possible ways of their implementation need to be investigated.
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The Pathway to Inquiry-Based Teaching : An European Perspective

The Pathway to Inquiry-Based Teaching : An European Perspective

The aim of this presentation is to offer an overview of recent educational research about the effects of classroom interventions on interest, motivation or attitude (I/M/A) toward science and technology (S&T). This synthesis has been conducted as a part of a larger review that implicated a systematic description of 228 research articles about I/M/A towards S&T that has been carried out by the Chaire de recherche sur l’intérêt des élèves { l’égard des sciences et de la technologie (CRIJEST). Selected articles were indexed in the ERIC database and published between 2000 and 2012. They were analysed with a grid composed of 36 multi-choice and open-ended items about the general information of each article and of its content : 1) type and scope, 2) evoked and defined I/M/A theoretical constructs, 3) description of the intervention that aimed at developing I/M/A, 4) research methods (variables, tools used, sample, etc.), 4) results. Among all the interventions that had been studied in the selected articles, five categories were considered: 1) hands-on activities, 2) inquiry-based learning, 3) use of information and communication technologies (ICT), 4) collaborative work, 5) contextualization. Although many of the articles reported comparative results (before/after, with/without intervention), few of them merely reported results obtained with only one questionnaire or survey that contained questions that referred to improvements of I/M/A. Most of the interventions had positive effects on students’ I/M/A. For example, inquiry-based learning tended to favour I/M/A not only because students could manipulate objects or instruments, but because of their cognitive involvement in the tasks they performed. It also appeared that a good contextualization of content knowledge to be taught (for example, linking content with real-world issues, real phenomena or current events) appeared to be important in order to get students interested. Based on this synthesis’ findings, conclusions and recommendations for future research about classroom interventions and their effects on I/M/A will be formulated.
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Inquiry and problem based pedagogy: Evidence from 10 field experiments

Inquiry and problem based pedagogy: Evidence from 10 field experiments

Keywords: Education, pedagogy, teacher effectiveness, mathematics, science, elementary education, inquiry-based learning, problem-based learning, early education. JEL Codes: C93, I25, I38, O15 Acknowledgments: We gratefully acknowledge the outstanding research assistance of Gabriel Englander. The authors are thankful to the Inter-American Development Bank and the Government of Japan for funding the research presented in this paper. The opinions expressed in this publication are those of the authors and do not necessarily reflect the views of the Inter-American Development Bank, its Board of Directors, or the countries they represent. The authors have no conflicts of interests or financial or material interests in the results. Registry numbers: (i) Paraguay 2011 and 2013 IPA IRB Protocol #: 241.11May-007 and AEA RCT # [AEARCTR-0002947]; (ii) Peru 2012 Mathematics IPA IRB Protocol #: 12February-003 and 2014 IPA IRB Protocol #: 212.10April-002 for 2012 both with AEA RCT # [AEARCTR- 0000365]; (iii) Peru Science 2014 Mathematics IPA IRB Protocol #: 12February-003 and AEA RCT#[AEARCTR-0000379]; (iv) Peru Science 2012 IPA IRB Protocol #: 215.10April-002 and AEA RCT#[AEARCTR-0002960]; (iv) Belize [ISCR/H/2/71] and AEA RCT#[AEARCTR-0002959]. The data for Argentina was provided to the authors by the government of Argentina, who executed the implementation. Thus, we do not have registry or IRB information.
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Inquiry-Based Teaching in the Content and Language Integrated Learning (CLIL) Classroom / Christine Orkisz Lang

Inquiry-Based Teaching in the Content and Language Integrated Learning (CLIL) Classroom / Christine Orkisz Lang

This study looks at three different areas of effectiveness in a CLIL instructional setting: effectiveness of learners‘ inquiry skill development, especially higher level criti[r]

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Game-Based Learning. Spielend Lernen?

Game-Based Learning. Spielend Lernen?

gen des Lernenden im Umgang mit dem Spiel, den im Spiel existierenden Regeln und Zielen und der Über- setzungskompetenz des Spielenden zwischen den Bedeutungskontexten von objektiver Realität und vom Medienspielraum abhängen. Der Einsatz von digitalen Lernspielen kann aufgrund der individuellen Spiel- erfahrungen die Erreichung festgelegter Lernziele nicht garantieren. Um auf definierte Lernziele hinwirken zu können, wäre demnach im Vorfeld eine individuelle Beeinflussung der Erwartungshaltung der Lernen- den durch eine pädagogische Betreuung erforderlich. Auch müsste die Übersetzungskompetenz der Lernen- den auf Defizite oder Unterschiede überprüft werden; der Lehrende wird somit zu einem/einer unverzicht- baren Lernprozessbegleiter/in, ohne den/die nach Wagner im Allgemeinen ein selbstgesteuertes Lernen mit- tels (Digital) Game-Based Learning weitgehend ausgeschlossen ist. Auch andere Autoren/innen (Kerres et al., 2009) erkennen die Notwendigkeit einer didaktischen Rahmung an, um gewünschte Lerneffekte erzie- len zu können. Garris und Driskell (2002) sehen zudem in der Nachbesprechung („De-Briefing“) eines Lernspiels einen kritischen Teil der Spielerfahrung, weil hier eine Verbindung von Spielwelt und Realität hergestellt werden kann: Die Lernenden können auf Parallelen zur Wirklichkeit aufmerksam gemacht wer- den und die Ereignisse des Spiels mit ihren Dozierenden kritisch reflektieren.
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Semantic and Structural Analysis of Web–based Learning Resources - Supporting Self–directed Resource–based Learning

Semantic and Structural Analysis of Web–based Learning Resources - Supporting Self–directed Resource–based Learning

During the learning process the learner may attach found information in web resources to the set goals and rate their relevance for the respective goal. As the learner’s information need often is quite specific, just storing a whole web resource is usually not enough. Instead, the possibility to extract only the relevant part of the information is more target–oriented towards the real learning goal. Thus, the selected fragment (called snippet) of an imported web resource is stored in the goal’s metadata; learners can access that relevant information later without having to access the original web page. Monitoring the learning process is supported by multiple scaffolds, e.g. setting the progress of attainment of a certain goal and displaying the goal hierarchy in combination with the already found web resources. Both stimulate the learner to contemplate where in the learning process she is right now, which goals she has already achieved and what goals are still open. In order not to lose focus on the goal the learner is following right now, in the 2 nd version of ELWMS.KOM it is possible for her to activate one goal at a time. This goal is displayed prominently, giving a reminder not to go astray and antagonizing the well–known lost–in–hyperspace phenomenon (experiencing disorientation due to information overload and aimlessly following hyperlinks [55]). Further, all goals and found resources can be displayed as a knowledge network (see figure 6.5) and an outline displaying all goals and resources. This enables the learner to reflect on already found information and the current course of action. Is the learner aware of her inefficient advance, she may alter her search behaviour according to her current situation –– for example by defining new goals, re–structuring her goal hierarchy or focusing on other goals that are more promising at the moment. Hence, during the search the processes of monitoring and regulation are supported.
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Verkaufstraining in der Augenoptik mit Game-Based Learning

Verkaufstraining in der Augenoptik mit Game-Based Learning

Einer der wahrscheinlich wirtschaftlich gesehen wichtigsten Vorteile ist die Ersparnis von Zeit, Personal und vor allem Geld. Die relativ hohen Kosten, die bei der Erstellung von E-Learning-Produkten, wie dem Edugame anfallen, werden mehr als aufgewogen. Denn die einmal produzierten Inhalte können jederzeit aktualisiert und repliziert werden. Ebenso fallen die Kosten für den Lehrenden, sowie jegliche Anfahrtskosten, im Vergleich zum Präsenzunterricht, weg bzw. werden verringert. Ein weiterer großer Vorteil ist mit Sicherheit die Flexibilität des E-Learning. Zu Zeiten des Smartphone und Tablet-PC's haben die Menschen jederzeit Zugriff auf das Internet und die damit verbundenen multimedialen Lernmöglichkeiten. Die Teilnehmer können also zeitlich und räumlich unbegrenzt auf die Lerninhalte zugreifen. Allerdings ist das auch kritisch zu betrachten, denn so sind die Lernenden gezwungen ihre Weiterbildung neben dem Alltag zu organisieren, was wiederum sehr viel Eigeninitiative voraussetzt.
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Game-based Learning : der Prof. mit der Pappnase?

Game-based Learning : der Prof. mit der Pappnase?

Edutainment setzt sich aus den Begriffen Education und Entertainment zusammen. En- tertainment ist dabei die Ausgangsbasis, Wissen wird quasi nebenbei vermittelt. Den Ansatz gibt es bereits seit ca. 20 Jahren und üblicherweise sind Edutainmentformate eher für die breite Masse als für ein spezialisiertes Publikum gedacht – also zunächst nicht für die universitäre Ausbildung. Allerdings gibt es auch eine weitere Interpretation des Be- griffes – hier stellt Edutainment jede Form der Verbindung von Spielen und Lernen dar, wäre damit ein Überbegriff für Game-based Learning [URL04] (dort beispielsweise be- zeichnet als Edutainment PC-Produkt) und die Basis für eine ganze Reihe weiterer Wortneuschöpfungen. Im Folgenden wird Edutainment nicht weiter betrachtet.
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Adaptive prototype-based dissimilarity learning

Adaptive prototype-based dissimilarity learning

Experiments are done within a 10−fold cross validation and with 10 repeats. We report the mean and standard deviation of the error on the test sets. For AC-RGLVQ label prediction is based on the label with the highest p-value. Further we provide values for the model complexity, by means of the number of points used to represent the prototypes or, in case of SVM, the number of support vectors in the full-class model (see Table 6.1). For SVM we provide results where the proximity matrices have been processed as mentioned before to obtain metric similarities using clipping or flipping. This procedure has a complexity of O(n 3 ) but is necessary for kernel machines. For comparison we also tried to obtain models without a costly eigenvalue correction (indicated by no) but failed for SVM due to convergence issues. Instead we provide some obtained results using a core vector machine (CVM) [99]. Theoretically CVM also can be used only for psd matrices but is less sensitive with respect to non psd matrices as long as the negative eigenvalues are small or not so relevant. For the ProDom data the negative eigenvalues are a substantial part of the data space, with a similar scale as the positive eigenvalues and it was not possible to run a kernel machine on the unprocessed proximity data.
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Machine learning based myoelectric control

Machine learning based myoelectric control

Significant research has been conducted in the past decades to overcome these limita- tions, mainly focusing on classification-based approaches. But these efforts had almost no impact on the clinical practice so far. The main reason for this is the lack of reliability under real-world conditions. In this thesis it is demonstrated that the reliability and ro- bustness of the classification-based approach can be significantly increased by means of optimized spatial filters, which enhance the signal characteristics in raw-signal domain. As the classification-based approach has still limitations regarding the flexibility of combining different motions, regression-based control techniques are explored, which allow for an independent simultaneous and proportional control of multiple DOFs. Four control methods are analyzed offline with a special focus on clinical applicability, namely linear regression (LR), mixture of linear experts (ME), multilayer perceptrons (MLP) and kernel ridge regression (KRR). Results show that the simple and computationally efficient methods LR and ME can perform as well as the more complex non-linear methods MLP and KRR if a proper feature representation is used. Furthermore, two DOFs of the wrist are linearly separable, which allows to estimate combined motions with high precision, even when trained with non-combined movements only.
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Efficient Preference-based Reinforcement Learning

Efficient Preference-based Reinforcement Learning

In the previous chapter, we have shown that preference-based reinforcement learning (PBRL) is substantially limited by the problem that we can not obtain feedback for every state-action along the sampled trajectories. Furthermore, we can not obtain feedback without asking the expert explicitly. Hence, we want to investigate methods that allow better approximations of state-action outcomes and generalize to trajectories that have not been explicitly evaluated. Util- ity functions (cf. Section II.5.3.a) are a possible solution as they describe a continuous model that can be learned from preferences. Additionally, PBRL algorithms usually run in cycles (cf. Sec- tion III.2.1), but learning a policy is a problem that can be solved independently if we can access numeric utilities. The iterative process is only required to solve the exploration/exploitation dilemma, introduced in Section II.2.2.b. In case sufficient samples to calculate an approximate policy are available, further sample collection is not required. Hence, when using a data ba- sis that is large enough to be able to assume a sufficient sample count, we can view the policy optimization process as a batch-learning problem. This enables us to analyze the utility learn- ing problem in more detail, without considering the influence of the exploration process. For obtaining an even more focused setup, we use state (and action) preferences with long-term ex- pectation in this chapter (Section III.3.1), allowing us to circumvent the temporal assignment problem, mentioned in Section III.3.3.
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Dissimilarity-based learning for complex data

Dissimilarity-based learning for complex data

The 3-dimensional tracking of human and animal body movement is important in various areas of science. Researchers, for example in the fields of biology, medicine, robotics, or sports, investigate such data to reveal patterns and complex interaction rules in natural motion [101, 104, 32]. Since the precision and the availability of motion tracking tech- nology is increasing, intelligent analysis methods become necessary to assist researchers in identifying relevant information in large amounts of data. Although the raw data usually consists of multiple 3-dimensional vectors, the data precision and characteristics vary depending on the kind of tracking system. Today, many kinds of systems are avail- able, ranging from large expensive motion capturing setups involving several distributed cameras and delivering very robust data at a high spatial resolution, to less sophisti- cated, small, cheap, and mobile solutions using only a single camera. Hence, there is a variety of options available for researchers to gather motion data. However, regarding the automatic analysis of this complex data, there is no general recipe in order to extract high-level information. Tools for clustering and visualization (see overviews in e.g. [80], and [35, ch. 10 ]) are widely applicable and can make the data accessible for experts in order to gain motor-functional insights from complex motion scenarios. In this context, metric learning algorithms [54, 119, 43] offer useful features. On the one hand, the prototype-based clustering technique can be used to categorize motion patterns, yield- ing a classifier for later recorded data, while the resulting prototypes may reveal typical poses or patterns, since they can be interpreted directly. On the other hand, with the addition of metric learning, the most relevant joint angles or spatial correlations can be identified automatically.
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Effects of two differently sequenced classroom scripts on common ground in collaborative inquiry learning

Effects of two differently sequenced classroom scripts on common ground in collaborative inquiry learning

In order to illustrate the discourse structures and moves, an overview of all discourses in the field trip and post-field trip was presented with the help of a graphical coding analy- sis (Keefer et al. 2000 ) to visualize the effects of the two different script sequences on the regulative and inquiry processes. The labels for high- and low-level regulative and inquiry processes are abbreviated. Chi’s ( 2009 ) ICAP framework is applied to each unit of analysis to indicate if the activity is active, constructive or interactive. Essentially, the ICAP model hypothesizes a hierarchical organization of activity types and their learning effectiveness. The activity types evoke different cognitive processes and engagement behavior with inter- activity as better than constructive, and constructive activity is better than active activity. A green triangle indicates that the activity is interactive, an inverted black triangle repre- sents a not interactive activity, an orange rectangle means the activity is constructive and a dark blue circle represents active. Furthermore, for the PSGI classroom script, a red arrow indicates instances where individuals’ ideas were integrated into the collaborative inquiry process to negotiate shared understanding and to create new knowledge, and for the PISG classroom script, a blue arrow is used. Excerpts of students’ work at the individual level in both script conditions were also highlighted to discuss how the differently sequenced class- room scripts could have shaped the discourse moves at the small group level.
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