Abstract

Computer-Supported Collaborative Learning (CSCL) research has become pervasive in STEM (science, technology, engineering, and mathematics) education over the last several decades. Guided by sociocultural and social constructivist theories of learning, CSCL focuses on shared meaning making and is influenced by the three pillars of CSCL: enabling technologies, pedagogical designs, and modes of collaboration. This chapter identifies four different approaches or clusters to CSCL that involve different combinations of these pillars. Focusing on two of these clusters, this chapter (a) identifies robust themes in this field and (b) discusses the positive outcomes associated with these aspects of CSCL. Outcomes include learning gains, process improvements, and affective outcomes. Across clusters, results demonstrate that scaffolding and feedback in different combinations affect outcomes. Moreover, different combinations are used with learners at different ages and with different learning goals. Designing CSCL for different learning environments requires considering the complex system of learning environments that emerge from the interaction among contexts, learner characteristics, and learning activities.

Introduction

Many contemporary theorists characterize learning as that which is fundamentally social rather than individual (Danish & Gresalfi, 2018). Advances in computer technologies have enabled diverse modes of collaboration and set the stage for Computer-Supported Collaborative Learning (CSCL). CSCL refers to collaborative learning that is mediated in some way by computer technology (Stahl, Koschmann, & Suthers, 2014). It rests on three major pillars: the technologies that support and enable CSCL, the pedagogical designs that apply CSCL to learning, and the modes in which learners collaborate. In describing the goal of research in CSCL, Miyake (2007) argued that research and design of CSCL  environment must take "collaboration seriously, and implements and evaluates technological support to materialize effective learning designs" (p. 248), addressing three key foundations of CSCL. Similarly, Roschelle, Bakia, Toyama, and Patton (2011) have argued that we need to understand the compound resources at play in complex learning environments. By looking at different combinations of CSCL design elements, we move closer to being able to understand how to design for CSCL in different contexts. This chapter considers how different combinations of these pillars affect the outcomes of CSCL research with a focus on science, technology, engineering, and mathematics (STEM) education, where much CSCL research has been conducted (Jeong, Hmelo-Silver, & Jo, 2019).

CSCL: An Overview

The pillars of CSCL are the technology, the pedagogy, and the mode of collaboration. CSCL environments may be synchronous, that is, with learners collaborating at the same time, or asynchronous, with learners collaborating at different times (Jeong et al., 2014). Synchronous collaboration can be at a distance (e.g., web conferences), or it can be face-to-face. An example of synchronous face-to-face CSCL is secondary school students discussing simulations in their classroom together (e.g., Sinha, Rogat, Adams-Wiggins, & Hmelo-Silver 2015), whereas an asynchronous CSCL design can involve learners distributed across time and space (e.g., Yukawa, 2006).

Within CSCL, the focus is on learning through technology-mediated collaboration as a coordinated effort to build shared knowledge (Stahl et al., 2014). A broad range of theoretical perspectives can apply (Hmelo-Silver & Jeong, 2021). However, because a general constructivist sociocultural orientation or sociocultural framework accounts for the majority of CSCL research, we ground our discussion in these latter frameworks, as they have been the dominant paradigms.

This chapter adopts a broad view on technology, focusing on the affordances and supports rather than technical features that these technologies provide for collaborative learning. Jeong and Hmelo-Silver (2016) proposed seven affordances of CSCL for learning. Affordances here refer to the ways technology mediates learning in CSCL. CSCL technologies provide learners opportunities to (a) engage in a joint task, (b) communicate, (c) share resources, (d) engage in productive collaborative learning processes, (e) engage in co-construction, (f) monitor and regulate collaborative learning, and (g) find and build groups and communities. Different combinations of these functions can be used in CSCL designs to support a range of instructional designs and pedagogical approaches.

Effects of CSCL on Learning

Recent meta-analyses suggest that CSCL has significant effects on student learning. Chen, Wang, Kirschner, and Tsai (2018) examined the role of collaboration, computer use, and overall CSCL environments on learning. They found overall moderate effects of CSCL on learning outcomes and social interaction, with large effects on group tasks. Vogel, Wecker, Kollar, and Fischer (2017) focused on scaffolding with CSCL scripts. They found small effects on knowledge gains and a moderate effect on collaboration skills. Scripts were particularly effective for learning domain knowledge when they prompted learners to engage in activities that built on the contribution of other group members or when they provided additional content-specific support. In a meta-analysis of CSCL in STEM domains, Jeong et al. (2019) found a similar overall moderate effect size. They did find, however, that effect sizes were affected by types of technology and pedagogy, education levels of learners, and modes of collaboration. For example, representational tools (e.g., simulations, modeling tools) were more effective in face-to-face than in asynchronous settings, as was inquiry learning. The use of scripts and discussion boards were more effective in asynchronous settings.

These syntheses suggest that CSCL is effective. However, these syntheses found that different factors moderated the effectiveness of these approaches. Jeong et al. (2019) drew from a larger corpus of CSCL research that was coded for types of technologies, pedagogies, and collaboration modes (c.f.,McKeown, Hmelo-Silver, Jeong, Hartley, Faulkner, & Emmanuel, 2017). They found that there was not just one CSCL but rather four unique clusters of CSCL designs:

• Face-to-face Inquiry with Dynamic Feedback— face-to-face collaboration, inquiry and exploration pedagogies, and dynamic or other tools.
• Online Generative Inquiry— asynchronous or face-to-face collaboration, inquiry and exploration or teacher-structured pedagogies, and sharing and co-construction technology.
• Asynchronous Teacher-Structured Discussion— asynchronous collaboration, discussion or teacher-structured pedagogies, and asynchronous communication technologies.
• Synchronous Collaboration—synchronous collaboration and communication technologies.

Here we focus on the first two inquiry-oriented clusters to show how CSCL has been used in different learning designs. This focus was selected because these were among the most commonly identified clusters and they provide a useful design contrast in considering how inquiry-oriented pedagogies are used with different technologies.

Face-to-Face Collaborative Inquiry with Dynamic Feedback (F2FCI)

This cluster emphasizes face-to-face collaboration with inquiry and exploration pedagogies using dynamic technological tools such as simulations, games, and immersive technology. These provide feedback based on learner actions as well as rich contexts. In addition, a substantial number of the papers in this cluster also used sharing and co-construction tools. Within the cluster, the majority of papers were in K-12. 

Outcomes

Learning under this type of CSCL led to significant learning gains, promoted student engagement, and supported positive process outcomes such as critical thinking and reasoning skills. These outcomes cut across quantitative and qualitative studies, disciplinary content, and education levels. K-12 math students improved their problem-solving skills (e.g., Roschelle, Rafanan, Estrella, Nussbaum, & Claro, 2010; Sao Pedro, Baker, & Rodrigo, 2014), conceptual understanding (Lai & White, 2012; Turcotte, 2012), and group collaboration (Chen et al., 2012). In physics, positive effects on learning gains were found in primary and secondary education (Turcotte, 2012; Echeverría et al., 2012, respectively). Primary students experienced positive learning gains and improved critical thinking skills from designing digital science games (Yang & Chang, 2013). Primary students who were guided either with awareness tools or scripts learned more about photosynthesis through a drawing task than students in a control condition (Gijlers et al., 2013).

F2FCI research also highlighted positive effects on student engagement and affective measures at multiple education levels. Primary students using handheld devices in an authentic outdoor learning task were enthusiastic and developed great interest in the assignment (Avraamidou, 2013). Secondary biology students who participated in a CSCL review game were more engaged than students in the control group who participated in traditional paper and pencil review sessions with CSCL support (Annetta, Minogue, Holmes & Cheng, 2009). Additionally, computer science secondary and tertiary students felt empowered in their own learning (Tsai, Tsai, & Hwang, 2012).

Furthermore, lessons using dynamic technologies with inquiry and exploration pedagogies promoted meaningful interactions between elementary students, which in turn led to greater learning outcomes (Lai & White, 2012). For example, students engaged in high quality interaction patterns which entailed discussing the problem, task delegation, and helping each other in turn complete more assignments correctly than students with poor communication and collaboration (Chen, Looi, Lin, Shao, & Chan, 2012).

Factors That Support Effectiveness

Overarching themes that emerged from this cluster are that both (a) pedagogies that support collaborative inquiry and (b) rich problem contexts that establish a joint task are needed to promote positive outcomes (e.g., Chiang, Yang, & Hwang, 2014; Kong, Yeung, & Wu, 2009; Lai & White, 2012). Authentic problem contexts can be set in games and simulations (e.g., Nelson & Ketelhut, 2008; Sinha et al., 2015). One way facilitators provided guided instruction was by giving assistance and feedback throughout collaborative inquiry, and by providing authentic problems for problem-based learning (e.g., Avraamidou, 2013).

Instructors provided guided instruction ranging from very open-ended to more highly-structured. For example, undergraduate and graduate students were given very open-ended guidelines as they engaged in mobile learning outside of the classroom (Tsai et al., 2012), whereas secondary-level students were provided more facilitation in a student-driven augmented reality game to help them learn electrostatics (Echeverría et al., 2012). Even greater structure was provided for primary students who were given systematic processes to follow as they engaged with inquiry learning to help them with knowledge sharing (Chiang et al., 2014). In a grade 5/6 study of Knowledge Forum, teacher and researcher questions were helpful in advancing student thinking (Turcotte, 2012).

Closely tied to the theme of guided inquiry is feedback (Hmelo-Silver et al., 2007). In studies with F2FCI with dynamic feedback, participants at a variety of educational levels received immediate feedback on a task or problem from facilitators (e.g., Kong et al., 2009;), peers (e.g., Lai & White, 2012), and/or software (e.g., Chen et al., 2012; Holmes, 2007; Roschelle et al., 2010). Software feedback could include direct hints or prompts or be more indirect in providing changes in the state of a simulation or game in response to learner actions (e.g., Eberbach & Hmelo-Silver, 2010). Teachers noted elementary student success with technology required active teacher feedback (Chiang et al., 2014; Kong et al, 2009).

Factors That Inhibit Effectiveness

Factors that may inhibit student learning and engagement are related to feedback. An example of the importance of informative feedback emerged from two studies with primary students and teachers. When teachers lack content expertise, the technology itself needs to have that content feedback embedded or risk leaving student questions unanswered (Kong et al., 2009). This is also a problem when a teacher is working with several groups and cannot provide consistent active feedback for each group (Chiang et al., 2014; Kong et al., 2009).

The lack of consistent, active feedback are pedagogical and technological concerns applicable at all educational levels. Technologies can be used to provide content feedback in such situations, but as Turcotte (2012) noted, just because technology provides affordances for particular kinds of activity such as elaborated explanations, learners do not always take advantage of those affordances.

Summary and Implications

In this cluster, there was a trend for students to be collaboratively engaged with authentic problems and their learning nurtured by guided instruction, feedback, and discussion. Together, these combinations were associated with significant learning gains, positive student engagement, meaningful interactions between students, and improved group collaboration and communication skills.

Simulation tools and augmented reality games allow students opportunities for practice, feedback, and revision as they collaboratively engage with disciplinary content and practices without the time or expense of physical tools. In this cluster, learning with authentic problems was supported by opportunities for guided inquiry and immediate feedback from the tools and discussion. Technology played a role in helping students to work in settings that are more authentic and have opportunities to directly test their ideas and solutions, with the tools providing dynamic feedback.The main difference between the higher education and K-12 school environments was the control retained by the instructor. When this design was used in higher education, students had greater autonomy than primary and secondary education students. Questions remain about how much information needs to be embedded in the technology and how to help teachers support their students.

Online Generative Inquiry (OGI)

This cluster was primarily concerned with integrated learning environments (e.g., learning management systems) or online sharing and co-construction technologies (e.g., wikis). Asynchronous collaboration with inquiry and exploration pedagogies was a main focus, but collaboration and pedagogy were more varied than in some of the other clusters. By nature, integrated environments offered a variety of tools that could be used to collaborate asynchronously or in face-to-face environments. Most OGI research focused on higher education, suggesting connections between learner education level and collaboration types. Communication and discussion occurred through sharing/co-construction tools and integrated environments that allowed direct communication through built-in chat tools or discussion forums.

Outcomes

Research in this cluster primarily reported process gains as well as some learning gains. The positive process gains included metacognitive skills supported by a knowledge-building environment (Pifarre & Cobos, 2010) and improved reasoning and collaboration via e-learning environments or wikis (Huang, & Nakazawa, 2010). In an undergraduate statistics course, student report writing was completed individually or collectively via a wiki (Neumann & Hood, 2009). There were no differences in terms of final report quality, but students who collaborated within wikis were more engaged and had higher attendance than those who worked alone.

Learning gains in this cluster were not uniform. On one hand, collaborative use of a multimedia-enriched concept map produced greater short-and long-term retention scores than a control group that received regular instruction and worked on assignments individually (Marée et al., 2013). However, another study found no differences between the final grades of a group that collaborated through wikis and a group that worked independently with a word processor, despite positive engagement (Neumann & Hood, 2009). Here, some students reported dissatisfaction with using the technology, and task completion could be negatively affected by low group member participation. Mixed learning gains were reported in Krause, Stark, and Mandl (2009) in examining the role of adaptive feedback in an asynchronous statistics class. They found that feedback was beneficial for students with low prior knowledge but had no effect on students with high prior knowledge.

Factors That Support Effectiveness

In a wiki co-construction environment, students reported more interaction with peers than with their instructor, and that the instructor moved to more of a moderator role, allowing students to initiate interactions (Huang & Nakazawa, 2010). Students also noted the importance of receiving public feedback about revisions within the wiki where these could be discussed by group members. This feedback functioned as collaborative scaffolding and an anchor for their discussions. In using representational tools, Marée, van Bruggen and Jochems (2013 when there was less teacher guidance.

This OGI research also offered some promising implications about specific technologies and pedagogical practices. For example, in asynchronous discussion threads (i.e., a technology), particularly when students act as facilitators (i.e., a pedagogical practice), they need to understand different types of thread patterns and how questioning, summarizing, pointing, and resolving may affect discussion thread development and closure (Chan, Hew, & Cheung, 2009). Feedback, whether from instructors or peers, may promote more reflection--especially when it offers explanations (Krause et al., 2009). Thus, regardless of the source, feedback should be thoughtful, thorough, and encourage students to go beyond remembering information. Pifarre and Cobos (2010) demonstrated the importance of scaffolds in improving peer questioning and co-regulation.

Much of this research investigated how students used and perceived specific technology. These suggest that the use of collaborative group activities, instructors’ timely feedback, and support materials embedded within an integrated system all related to student satisfaction with a variety of STEM related vocational e-learning courses (Inayat, ul Amin, Inayat, & Salim, 2013). When guided instruction and immediate feedback are integrated within these pedagogies and technologies, it can lead to improved student learning (Krause et al., 2009; Marée et al., 2013) and task completion (Hämäläinen, & Arvaja, 2009).

Although scripts might be effective for task completion, they do not necessarily avoid variability in collaboration processes among groups. In a study of university students engaging in case-based learning, Hämäläinen and Arvaja (2009) still found differences in collaborative activity with unequal participation or a dominant group member. This suggests that the structure from script may not be sufficient to promote uniformly productive collaboration.

Factors That Inhibit Effectiveness

Again, feedback was mentioned in relation to factors that inhibit effectiveness. Consistent with findings in other clusters, a lack of feedback can negatively affect students’ learning outcomes (Krause et al., 2009). Meanwhile, too much feedback, or using facilitation techniques that resolve conflicts or summarize key points can lead to discussions closing prematurely (Chan et al., 2009). Without enough guidance regarding the importance of positive collaboration, students may have high task activity but not necessarily high-quality collaboration (Hämäläinen, & Arvaja, 2009).

Summary and Implications

Timely guidance from teachers and peers plays an important role in increasing student outcomes as well as favorable perceptions of the environment. The results for this cluster also highlighted the importance of keeping the guidance at an optimal level.

In contrast to F2FCI, communication was heavily mediated in this cluster. It made students’ thinking visible in ways that a face-to-face classroom may not allow. Teachers can thus follow persistent threads of discussion along with the artifacts being created. This gives teachers opportunities for ongoing formative assessment and may also provide grist for student reflection on these ongoing interactions in ways that face-to-face discussions may not. This may be particularly important in higher education contexts with their larger class sizes that might otherwise offer few opportunities for discussion and feedback.

Discussion

It is clear that the three pillars of CSCL—collaboration, technology, and pedagogy—are used in different combinations to design effective learning environments. However, we need to better understand how to design for the balance between developing appropriate structures and supporting student agency in ambitious learning practices promoted by CSCL (Glazewski & Hmelo-Silver, 2019). This is particularly important in being able to support diverse learners (Uttamchandani et al., 2020). We review this in the context of the major issues this chapter has identified.

First, feedback and support are themes that run through all the clusters, whether the feedback comes from the teacher, peers, or tools. Questions about feedback consider both timing and quality. Poorly timed feedback that does not address appropriate content, skills, or practices may impede learning. In designing effective CSCL, it is important to think about feedback and support as part of the CSCL system of technologies, pedagogies, and collaboration modes. It is important to consider which aspects of feedback and support should be fixed and part of the environment and which should be adaptive to the needs of the situation. Much dynamic feedback needs to come from teachers and peers. Not enough research has addressed ways to support high quality peer feedback (De Wever, Van Keer, Schellens, & Valcke, 2010). Research on scripts and roles may be one way to scaffold students to provide good quality feedback to their peers. To support teacher feedback, CSCL environments should provide mechanisms for teachers to monitor multiple groups, identify challenges that groups might face, and provide appropriate feedback and resources.

Second, certain technologies lend themselves better to particular communication channels and/or pedagogical goals. Dynamic representational tools are generally used in face-to-face environments as the F2FCI Cluster demonstrates. Rapid cycles of activity and engagement with such tools lend themselves to the immediacy of being in the same place at the same time. Additionally, the tools allow for deictic referencing as learners can easily point to phenomena on-screen and observe the gestures of others. Effect sizes were larger when dynamic representational tools were used in face-to-face settings (Jeong et al., 2019). Similarly, the use of sharing and co-construction tools dominated the OGI cluster. These tools may be more critical for online environments because learners’ interaction channels are limited and thus need to be mediated by communication tools. When communicating and collaborating with these tools, learners need to be more explicit about their actions and contributions, which can provide opportunities for reflection, thus fostering knowledge co-construction .

Third, different learning environments are used for different learners. CSCL involving younger learners tends to involve face-to-face collaboration rather than online collaborations. Online collaboration requires dealing with a broader range of communication modalities and as such may be used for more mature learners. The trend seems to be for more structure and face-to-face collaboration for younger learners, perhaps due to the need for social presence in this population as they tend to be in the same physical space. In addition, technology tools can add to cognitive demands and pose increasing challenges for regulation that may be difficult for younger learners. However, these challenges are not unique to younger learners. Creating social presence and supporting self-regulated learning is challenging even for more mature learners in online environments.

Implications for LIDT

Considerations for Practice

Helping stakeholders become aware of the usefulness of CSCL is a first step in implementing evidence-based practices. This includes reporting on CSCL in practitioner venues publications. In addition, professional development training is important for instructors in order to effectively implement CSCL. Facilitating CSCL requires mastering the technology, tailoring it to tasks, and providing adequate scaffolds that can be differentiated for student skills and prior knowledge. 

CSCL as a Complex System

It is critical to consider CSCL as a system of compound resources (Roschelle et al., 2011). There is no one-size-fits-all solution; how CSCL is used in different learning environments needs to be tailored to the particular level of the learners and the learning goals. Designers and teachers will need to consider how the collaboration modes, technology, and pedagogical choices fit together in ways that are more than the sum of their parts. A consideration of the seven CSCL affordances can help them to directly design efforts along with considering the learning contexts and educational goals.

LIDT in the World

While you watch this video, pay attention to how the technology is being used to facilitate collaboration:

Write a paragraph or two reflecting on how the technology in this video reflects what you read in this chapter. Here are some questions you may want to think about:

• What are the benefits or drawbacks to implementing technology like this in the classroom?
• Is it sustainable? Why or why not?
• Do you think this technology would be received as well in classrooms with older learners?
• Can the assignment of this technology be flexible enough to fit in different pedagogies?
• Is the use of this technology compatible to a variety of learning environments?

Acknowledgements

This work was supported by the US National Science Foundation [Grant # 1249492]; and the National Research Foundation of Korea [Grant # NRF-2016R1D1A1B03935697]. We thank Jessica McKeown for her contributions to this synthesis. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the funding agencies.

References

Annetta, L. A., Minogue, J., Holmes, S. Y., & Cheng, M. T. (2009). Investigating the impact of video games on high school students’ engagement and learning about genetics. Computers & Education, 53, 74-85.

Avraamidou, L. (2013). The use of mobile technologies in project-based science: A case study. Journal of Computers and Mathematics and Science Teaching, 32, 361-379.

Chen, J., Wang, M., Kirschner, P. A., & Tsai, C.-C. (2018). The role of collaboration, computer use, learning environments, and supporting strategies in CSCL: A meta-analysis. Review of Educational Research. doi:10.3102/0034654318791584.

Chan, J. C. C., Hew, K. F., & Cheung, W. S. (2009). Asynchronous online discussion thread development: examining growth patterns and peer‐facilitation techniques. Journal of Computer Assisted Learning, 25(5), 438-452.

Chen, Y. H., Looi, C. K., Lin, C. P., Shao, Y. J., & Chan, T. W. (2012). Utilizing a collaborative cross number puzzle game to develop the computing ability of addition and subtraction. Educational Technology & Society, 15, 354-366.

Chi, M. T. H., & Wylie, R. (2014). The ICAP framework: Linking cognitive engagement to active learning outcomes. Educational Psychologist, 49(4), 219-243.

Chiang, T. H.C., Yang, S. J.H., Hwang, G. (2014). Students’ online interactive patterns in augmented reality-based inquiry activities. Computers & Education, 78, 97-108.  

[Compugen Inc.]. (2019, March 1). Creating an Inclusive and Collaborative Environment in the Classroom [Video]. YouTube. https://www.youtube.com/watch?v=hgnuj3M9MbI

Danish, J. A. & Gresalfi, M. (2018). Cognitive and sociocultural perspectives on learning: Tensions and synergy in the learning sciences. In F. Fischer, C. E. Hmelo-Silver, S. R. Goldman, & P. Reimann. International Handbook of the Learning Sciences (pp. 33-43). New York, NY: Routledge.

De Wever, B., Van Keer, H., Schellens, T., & Valcke, M. (2010). Structuring asynchronous discussion groups: Comparing scripting by assigning roles with regulation by cross-age peer tutors. Learning and Instruction, 20, 349-360.

Eberbach, C., & Hmelo-Silver, C. E. (2010). Observing the seen and unseen: Computer and social mediation of a complex biological system. In Z. C. Zacharia, C. P. Constantinou, & M. Papaevripidou (Eds.), Computer Based Learning in Science (pp. 213-224). OEliZK.

Echeverría, A., Améstica, M., Gil, F., Nussbaum, M., Barrios, E., & Leclerc, S. (2012). Exploring different technological platforms for supporting co-located collaborative games in the classroom. Computers in Human Behavior, 28, 1170-1177.

Gijlers, H., Weinberger, A., van Dijk, A. M., Bollen, L., & van Joolingen, W. (2013). Collaborative drawing on a shared digital canvas in elementary science education: The effects of script and task awareness support. International journal of computer-supported collaborative learning, 8(4), 427-453.

Glazewski, K. D. & Hmelo-Silver, C. E. (2019). Scaffolding and Supporting Use of Information for Ambitious Learning Practices. Information and Learning Sciences, 120 (1/2), 39-58.

Hämäläinen, R., & Arvaja, M. (2009). Scripted collaboration and group‐based variations in a higher education CSCL context. Scandinavian Journal of Educational Research, 53, 1-16.

Hmelo-Silver, C. E., & Jeong, H. (2021). Benefits and Challenges of Interdisciplinarity in CSCL Research: A view from the literature [Review]. Frontiers in Psychology, 11(3754), 11. https://doi.org/10.3389/fpsyg.2020.579986

Holmes, J. (2007). Designing agents to support learning by explaining. Computers & Education, 48, 523-547.

Huang, W. H. D., & Nakazawa, K. (2010). An empirical analysis on how learners interact in wiki in a graduate level online course. Interactive Learning Environments, 18, 233-244.

Inayat, I., ul Amin, R., Inayat, Z., & Salim, S. S. (2013). Effects of collaborative web based vocational education and training (VET) on learning outcomes. Computers & Education, 68, 153-166.

Järvelä, S., & Hadwin, A. F. (2013). New frontiers: Regulating learning in CSCL. Educational Psychologist, 48(1), 25-39.

Jeong, H., & Hmelo-Silver, C. E. (2016). Seven affordances of CSCL Technology: How can technology support collaborative learning. Educational Psychologist, 51, 247-265.

Jeong, H., Hmelo-Silver, C. E., & Yu, Y. (2014). An examination of CSCL methodological practices and the influence of theoretical frameworks 2005–2009. International Journal of Computer-Supported Collaborative Learning, 9(3), 305-334.

Jeong, H., Hmelo-Silver, C. E., & Jo, K. (2019). Ten Years of Computer-Supported Collaborative Learning: A meta-analysis of CSCL in STEM education during 2005-2014. Educational Research Review, 100284.

Kong, S. C., Yeung, Y. Y., & Wu, X. Q. (2009). An experience of teaching for learning by observation: Remote-controlled experiments on electrical circuits. Computers & Education, 52, 702-717.

Krause, U. M., Stark, R., & Mandl, H. (2009). The effects of cooperative learning and feedback on e-learning in statistics. Learning and Instruction, 19, 158-170.

Lai, K., & White, T. (2012). Exploring quadrilaterals in a small group computing environment. Computers & Education, 59, 963-973.

Lakkala, M., Lallimo, J., & Hakkarainen, K. (2005). Teachers’ pedagogical designs for technology-supported collective inquiry: A national case study. Computers & Education, 45, 337-356.

Marée, T. J., van Bruggen, J. M., & Jochems, W. M. (2013). Effective self-regulated science learning through multimedia-enriched skeleton concept maps. Research in Science & Technological Education, 31, 16-30.

McKeown, J., Hmelo-Silver, C. E., Jeong, H., Hartley, K., Faulkner, R., & Emmanuel, N. (2017). A Meta-Synthesis of CSCL Literature in STEM Education. In B. K. Smith, M. Borge, E. Mercier, & K.-Y. Lim (Eds.), Proceedings of CSCL 2017. Philadelphia, PA: International Society of the Learning Sciences.

Miyake, N. (2007). Computer supported collaborative learning. In R. Andrews & C. Haythornwaite (Eds.), Sage Handbook of E-learning Research (pp. 248-266). London UK: Sage.

Neumann, D. L., & Hood, M. (2009). The effects of using a wiki on student engagement and learning of report writing skills in a university statistics course. Australasian Journal of Educational Technology, 25, 382-398.

Pifarre, M., & Cobos, R. (2010). Promoting metacognitive skills through peer scaffolding in a CSCL environment. International Journal of Computer-Supported Collaborative Learning, 5, 237-253.

Roschelle, J., Rafanan, K., Estrella, G., Nussbaum, M., & Claro, S. (2010). From handheld collaborative tool to effective classroom module: Embedding CSCL in a broader design framework. Computers & Education, 55, 1018-1026.  

Roschelle, J., Bakia, M., Toyama, Y., & Patton, C. (2011). Eight issues for learning scientists about education and the economy. Journal of the Learning Sciences, 20, 3-49.

Sao Pedro, M., Baker, R. S., & Rodrigo, M. M. T. (2014). Carelessness and affect in an intelligent tutoring system for mathematics. International Journal of Artificial Intelligence in Education, 24(2), 189-210.

Shaw, R. S. (2013). The relationships among group size, participation, and performance of programming language learning supported with online forums. Computers & Education, 62, 196–207.  

Sinha, S., Rogat, T., Adams-Wiggins, K. R., & Hmelo-Silver, C. E. (2015). Collaborative group engagement in a computer-supported inquiry learning environment. International Journal of Computer-Supported Collaborative Learning, 10, 273-307.

So, H. J., & Brush, T. A. (2008). Student perceptions of collaborative learning, social presence and satisfaction in a blended learning environment: Relationships and critical factors. Computers & Education, 51, 318-336.

Stahl, G., Koschmann, T., & Suthers, D. D. (2014). Computer-supported collaborative learning. In R. K. Sawyer (Ed.), Cambridge Handbook of the Learning Sciences (2nd ed., pp. pp. 479-500). NY: Cambridge University Press.

Tsai, P. S., Tsai, C. C., & Hwang, G. J. (2012). Developing a survey for assessing preferences in constructivist context‐aware ubiquitous learning environments. Journal of Computer assisted Learning, 28, 250-264.

Turcotte, S. (2012). Computer-supported collaborative inquiry on buoyancy: A discourse analysis supporting the "Pieces" position on conceptual change. Journal of Science Education and Technology, 21, 808-825

Uttamchandani, S., Bhimdiwala, A., & Hmelo-Silver, C. E. (2020). Finding a place for equity in CSCL: Ambitious learning practices as a lever for sustained educational change. International Journal of Computer-Supported Collaborative Learning. 15, 373–382.

Van Amelsvoort, M., Andriessen, J., & Kanselaar, G. (2007). Representational tools in computer-supported collaborative argumentation-based learning: How dyads work with constructed and inspected argumentative diagrams. Journal of the Learning Sciences, 16 485-521.

Vogel, F., Wecker, C., Kollar, I., & Fischer, F. (2017). Socio-cognitive scaffolding with computer-supported collaboration scripts: A meta-analysis. Educational Psychology Review, 29, 477-511.

Yang, Y. T. C., & Chang, C. H. (2013). Empowering students through digital game authorship: Enhancing concentration, critical thinking, and academic achievement. Computers & Education, 68, 334-344.

Yukawa, J. (2006). Co-reflection in online learning: Collaborative critical thinking as narrative. International Journal of Computer-Supported Collaborative Learning, 1(2), 203-228.