I Am an American Ph.D. Student at the University of Twente in Enschede, the Netherlands

I am an American Ph.D. Student at the University of Twente in Enschede, The Netherlands. I work with Dr. Ton de Jong, Dr. Wouter van Joolingen, and Dr. Ard Lazonder. My research centers around development of a cognitive tool to support students to plan, monitor, and evaluate their learning within Co-Lab (see Co-Lab is an environment which seeks to bring systems dynamic modeling together with inquiry learning and simulations. Typically students have difficulty establishing, goals, monitoring their understanding, and progress, and evaluating their products and working method in environments such as Co-Lab. The process coordinator is a tool which we developed to assist students with these processes. This tool was designed based on the works of Lin, X., Hmelo, C., Kinzer, C., & Secules, T. (1999), Njoo, M., & De Jong, T. (1993), Van Joolingen, W.E., & De Jong, T. (1991) and White, B., & Frederiksen, J.R. (1998)- to name a few. We have conducted four studies with Co-Lab examining the effects of this tool on learning and on the learning process. Following, is a list of publications which explicate our research. I plan on defending my dissertation in the fall of 2007 and will seek employment in academic and non-profit communities.

As future chair of this SIG, replacing Linda Garavalia, I look forward to continuing to support the excellent team of volunteers and fellow officers who have expanded the activities of this SIG to include student awards, alternative business meeting formats, and putting together outstanding and interesting programs, newsletters, and listserv information. I hope in the coming year we can continue to hear and serve the membership of this SIG, and towards this end, I look forward to seeing you and hearing your ideas at our annual business meeting in Chicago’s AERA conference.

Publications:

Manlove, S., & Lazonder, A. (2004). "Self-regulation and collaboration in a discovery learning environment." Paper presented at the First Meeting of the EARLI-SIG on Metacognition, June 30 - July 2, Amsterdam, The Netherlands.

Manlove, S., Lazonder, A.W., & De Jong, T. (2006). "Regulative support for collaborative scientific inquiry learning". Journal of Computer Assisted Learning, 22(2), 87-98.

Van Joolingen, W.R., De Jong, T., Lazonder, A.W., Savelsbergh, E., & Manlove, S. (2005). "Co-Lab: Research and development of an on-line learning environment for collaborative scientific discovery learning." Computers in Human Behavior, 21(4), 671-688.

Selected References:

Lin, X., C. Hmelo, et al. (1999). "Designing Technology to Support Reflection." Educational Technology Research and Development 47(3): 43-62.

Njoo, M. and T. De Jong (1993). "Exploratory Learning With a Computer Simulation For Control Theory. Learning Processes and Instructional Support." Journal of Research in Science Teaching 30: 821-844.

Van Joolingen, W. R. and T. De Jong (1991). "Characteristics of Simulations for Instructional Settings." Education & Computing 6.

White, B. Y. and J. R. Frederiksen (1998). "Inquiry, Modeling, and Metacognition: Making Science Accessible to All Students." Cognition and Instruction 16(1): 3-118.

University of Wisconsin-Milwaukee.

Various self-regulation and motivation constructs have been studied extensively over the past few decades,with most research showing that these processes are key enablers of students’ adaptive academic outcomes (Bandura, 1997; Boekaerts, Pintrich, & Zeidner, 2000; DiPerna, Volpe, & Elliot, 2002; Pintrich & Schunk, 2002;). When students exhibit deficits in these processes they are not only at-risk for academic underachievement but are also more likely to exhibit maladaptive behaviors such as truancy or even dropping out of school. Although these latter outcomes can occur in any school district, they are commonly observed among disadvantaged, urban youth – a phenomenon likely due to the complex interplay of environmental and situational factors such as poverty, neighborhood violence, parental educational level, and family distress (Byrnes, 2003; Nettles, Mucherah, & Jones, 2000). Regardless of the nature of the school setting, however, preliminary evidence shows that both regular and special education teachers often feel ill-equipped to deal with such student problems and have expressed a strong desire to receive professional development training in these areas (Cleary & Zimmerman, 2006; Coalition for Psychology in School and Education, 2006, August). For example, the Coalition for Psychology in School and Education conducted a survey with over 2,300 teachers from 49 states (including the District of Columbia) to identify the specific domains of professional development which were most important for them to learn about. In short, the teachers indicated that training in instructional and classroom management skills were of primary interest, with “motivating students to learn” one of the most cited areas of professional need (Coalition for Psychology in School and Education, 2006, August).

Given that student motivation and self-regulation issues are at the forefront of many educational and research agendas, one may assume that school psychologists frequently evaluate youth who exhibit these types of problems. Recent research shows that although reasonable, it is highly likely that this assumption is incorrect. In an analog experimental study with 96 special education teachers, Cleary & Zimmerman (2006) showed that even though the teachers valued assessment information detailing student motivation and self-regulated functioning, they were rarely provided with such information in psychoeducational reports or in students’ Individual Education Programs (IEP). A more direct evaluation of school psychologist assessment practices provides more compelling support for the presence of this “practice gap” in school psychology (Cleary, 2007). In a recent survey with 108 school psychologists, while school-based practitioners frequently encountered students with motivation/self-regulation concerns (e.g., low effort, poor use of learning strategies, poor self-awareness or reflection), they rarely evaluated these processes in any formal or systematic manner (Cleary, 2007). At this point, the precise nature and underlying sources of this practice anomaly are not well-understood, although there is preliminary evidence suggesting that school psychologists possess a “knowledge deficit” in motivation/self-regulation assessments (i.e., low familiarity with common self-report or rating scales (e.g., MSLQ, LASSI, self-efficacy measures)) (Cleary, 2007)

Irrespective of the potential contributing factors, the existence of this practice gap takes on even greater significance when one considers the ever increasing rates of underachievement and academic disengagement (e.g., drop-out, truancy) among disadvantaged, minority youth (Byrnes, 2003; Cleary, 2006). If practitioners do not routinely target key processes such as students’ self-efficacy, use of learning strategies, or self-reflective processes (self-judgments, self-reactions), it is inherently more difficult to adequately plan for and to develop appropriate, individualized interventions. In other words, inadequate motivation and self-regulation assessments will often inhibit the ability of clinicians to meaningfully work with youth exhibiting these types of problems. Although research has identified many types of “evidence-based” self-regulation intervention programs (Boekaerts, Pintrich, & Zeidner, 2000; Butler, 1998; Graham, Harris, & Troia, 1998), there are relatively few comprehensive self-regulation and motivation programs that seek to link assessment to intervention and specifically target at-risk, urban adolescents. Future research needs to closely examine the specific professional needs of school-based practitioners relative to motivation/self-regulation assessments and to investigate how these types of intervention programs can be successfully implemented with diverse populations

References

Bandura, A. (1997). Self-efficacy: The exercise of control. New York: W.H. Freeman.

Boekaerts, M., Pintrich, P.R., & Zeidner, M. (Eds.). (2000). Self-regulation: Theory, research,and applications. Orlando, FL: Academic Press.

Butler, D. (1998). The strategic content learning approach to promoting self-regulated learning: A report of three studies. Journal of Educational Psychology, 90, 682-697.

Byrnes, J.P. (2003). Factors predictive of mathematics achievement in White, Black, and Hispanic 12th graders. Journal of Educational Psychology, 95, 316-326.

Cleary, T.J. (2006). The development and validation of the Self-Regulation Strategy Inventory – Self-Report. Journal of School Psychology, 44, 307-322.

Cleary, T.J. (2007). Evaluation of school psychologists’ motivation and self-regulation assessment practices. Poster session accepted for presentation at the 2007 Annual Convention of the National Association of School Psychologists,New York, NY.

Cleary, T.J., & Zimmerman, B.J. (2006). Teachers’ perceived usefulness of strategy microanalytic assessment information. Psychology in the Schools, 43, 149-155.

Coalition for Psychology in Schools and Education. (2006, August). Report on the Teacher Needs Survey.Washington, D.C.: American Psychological Association, Center for Psychology in Schools and Education.

Diperna, J.C., Volpe, R.J., & Elliot, S.N. (2002). A model of academic enablers and elementary reading/language arts achievement. School Psychology Review, 31, 298-312.

Graham, S., Harris, K., & Troia, G.A. (1998). Writing and self-regulation: Cases from the Self-Regulated Strategy Development Model. In D.H. Schunk & B.J. Zimmerman (Eds.). Self-regulated learning: From teaching to self-reflective practice.New York: Guilford Press.

Nettles, S.M., Mucherah, W., & Jones, D.S. (2000). Understanding resilience: The role of social resources. Journal of Education for Students Placed at Risk, 5, 47-60.

Pintrich, P.R., & Schunk, D.H. (2002). Motivation in education: Theory, research, and Applications (2nd ed.). Upper Saddle, NJ: Prentice-Hall, Inc.

Dr. Timothy Cleary is an assistant professor at the University of Wisconsin-Milwaukee. His primary research interests include developing and evaluating various forms of self-regulation/motivation assessments as well as studying the effectiveness of applied intervention programs for at-risk youth. He is currently evaluating the efficacy of his intervention program called Self-Regulation Empowerment Program. Dr. Cleary is also conducting a line of research exploring the assessment and intervention practices and professional development needs of practicing school psychologists.

Summary of an AERA 2006 SSRL-SIG Presentation

Overview of Cognition and Technology Laboratory (CTL) Research

Dr. Roger Azevedo

University of Memphis

Dr. Azevedo’s presentation at last year’s SIG focused on an overview of SRL about complex science topics with hypermedia. The overview of that talk focused on the examining students' self-regulated learning (SRL) while using web-based hypermedia learning environments to learn about complex science topics (e.g., the circulatory system and ecology). The research goals that were examined, included: 1) SRL across developmental levels (middle school, high school, and college students) and contexts (laboratory and classroom); (2) self- and co-regulation during individual and collaborative learning sessions; (3) the effectiveness of co-construction of learning goals while using hypermedia environments; and (4) web-based hypermedia environments as facilitators of students' SRL.

Significance

The broad scope of SRL appeals to educational researchers who seek to understand how students become adept and independent in their educational pursuits. Whether SRL is viewed as a set of skills that can be taught explicitly or as developmental processes of self-regulation that emerge with experience (within a domain, topic, or task), web-based hypermedia environments can provide opportunities to students of all ages that will help them become strategic, motivated, and independent learners in learning complex and challenging topics.

Multi-Method Approach to Examine SRL

We use true-experimental designs from psychology and other fields related to the learning sciences to empirically investigate the differences between different scaffolding conditions that have been designed to facilitate or impede students’ ability to regulate their learning. We also use think-aloud protocols from cognitive science to investigate students’ self-regulatory behavior during learning. Video and audio data provide process data on how students regulate their learning when they use hypermedia environments to learn about the circulatory system and ecological systems.

Results and Discussion

Our results suggest that hypermedia can be used to enhance the ability of students of different ages to learn about complex topics, provided that they are provided with adaptive scaffolding designed to regulate their learning. We have empirically demonstrated the effectiveness of adaptive scaffolding in facilitating middle school, high school, and undergraduate students’ learning as indicated by several learning measures. Adaptive scaffolding led to significant increases in students’ learning of the science topics and was more effective than providing students with no scaffolding, which led to more learning than providing students with fixed scaffolding. As for developmental levels, undergraduate, high school, and middle school students learned about the same amount of knowledge of the circulatory system. Also, we failed to find an interaction between scaffolding conditions and developmental levels, indicating that regardless of students’ ages, the three scaffolding conditions followed the same patterns of differential effects on all students’ learning about the circulatory system. However, we did find qualitative and quantitative differences in students’ use and deployment of self-regulatory skills during learning.

Application

Our results have implications for the design of embedded scaffolds for hypermedia environments designed to foster students' learning of complex topics. To this end, we could incorporate certain tutor scaffolding moves to emulate the role of the tutor in our studies. Our results also have implications for training students how to regulate their learning of complex and challenging topics. Lastly, this kind of training can be extended to pre-service teachers who will need to train their students how to regulate their learning with technology-based learning environments.

Brief Bio. Dr. Roger Azevedo received his Ph.D. in Educational Psychology and Applied Cognitive Science from McGillUniversity. After leaving McGill, he joined the Department of Psychology at CarnegieMellonUniversity to complete his postdoctoral training. He was an Assistant and tenured Associate Professor at the University of Maryland (Dept. of Human Development) from 1999-2006. In the Fall of 2006, he joined the Psychology Department and the Institute for Intelligent Systems at the University of Memphis (see as a faculty member in the area of cognitive psychology. Dr. Azevedo is interested in cognitive science, human and computer tutoring, self-regulated learning, metacognition, information processing, problem solving, knowledge representation and organization, learning about complex topics (e.g., biology, ecology), and the design of computer-based learning environments (CBLEs) as MetaCognitive tools for enhancing learning.

Mr. John Riveaux has a Baccalaureate in Fine Arts from the School of Visual Arts . He is pursuing a Master's in Art Education at QueensCollege, The CityUniversity of New York. Currently, he is an Art Teacher in the New York City Department of Education. He is a dedicated teacher committed to promote self-regulation of learning and self-efficacy beliefs among his students.

A Snap Shot of “The New Learning” Pedagogy Debate in the Netherlands

Sarah Manlove

University of Twente in Enschede

In the past year and a half, a large-scale educational improvement effort in the Netherlands has come under increasing criticism and debate. “New Learning”, as it’s known is both a policy, and pedagogical shift that’s taken place in the Dutch educational system for at least a decade. There is a lot of discussion about what “New Learning” is, as it’s used as an umbrella term to refer to many implementation, policy, and practitioner issues. However, at a pedagogical level it has been characterized by one Dutch scholar as the increased use of collaboration, inquiry, problem-based, and situated (e.g., school-to-work) learning experiences for students (Van der Werff, 2006). Its implementation sees particularly high school and vocational level students (aged 16-18) taking competency based lessons, sometimes loosely structured around group or partner work, and which emphasize work place related skills for a knowledge economy. All of these methodologies are espoused to place a heavier emphasis on student’s direction of their own cognitions during learning (de Jong, 2006). It is interesting then to examine this debate, and see where self-regulation research and efforts might be situated within the issues it is generating.

The current criticism and debate ranges over a variety of political and implementation issues. The worry of many scholars and practitioners is that such methodologies sacrifice basic knowledge for skills or job related training. The criticism has generated a parliamentary review of New Learning’s implementation and many are asking “Wasn’t the old way better?”. The old way being loosely defined as direct instruction coupled with individual learning in the traditional teacher-lead classrooms. Two articles in Pedagogische Studiën (vol 83, issue 1) a Dutch Journal for Education and Pedagogical research, show however that the question being asked in instructional approach debates is not necessarily “which pedagogical approach is better” but “What context, combination, and extent can approaches be optimized?”

Dr. Van der Werff’s (2006) article “Old or New Learning? Or If Preferred Simply Learning?” gave a literature review in which she drew conclusions about the success of collaborative, inquiry, and situated learning vs. individual and instructor lead approaches. Her conclusions lead to the idea that direct instruction is more effective then the other approaches, and that individual learning might be preferred over more traditional methods. In doing so she cites the works of Charney, Reder, and Kusbit (1990) which concluded in their research with an excel spreadsheet task, that inquiry learning was mostly inferior and less effective then direct instruction. She also cites the work of Klahr, Chen, en Toth 2001 as evidence that direct instruction was better for higher cognitive skills such as scientific reasoning, and Slavin’s (1994) meta-analysis to show that too few studies show positive effects of collaborative learning.

Dr. Ton de Jong, Head of the Dept of Instructional Technology at the University of Twente’s Behavioral Science Faculty wrote a response to this work, entitled: “Discussion: The New learning; New Learning and Old Knowledge: On the Existing Evidence for the Effectiveness of New and ‘Combined’ Forms of Learning” in which he argues that although Van der Werf’s examination was useful in the context of breaking down and identifying what “New Learning” could mean in terms of pedagogy, her reported findings could be viewed in a different light. For example, Charney et al (1990)’s work had three conditions, a tutorial where students work through the problem using step by step instruction, a problem solving condition, and an explorative condition. The difference between the last two conditions was simply that in the problem solving condition students were given goals (or maybe a better assignment description) and the explorative condition needed to set their own goals. Charney writes that “Problem solving requires the learner to figure out which procedure is most appropriate to solve the problem and then to use it. Effective exploration-based learning would involve these steps, too.” Ultimately the problem solving condition was found to work best. A closer look at these conditions would reveal that the most successful condition incorporated elements of both direct and inquiry (explorative) methodologies. He also goes on to state that follow up work of Klahr which actually concluded that inquiry learning combined with direct instruction worked better than pure unguided discovery in helping students learn “control of variables”, a cognitive strategy used in science learning during experimentation (Klahr and Nigam, 2004). Finally De Jong cites further meta-analysis work by Lou (2004) which found based on independent findings from 71 studies, with experimental or statistical controls, that students learning with computers in small groups performed more of a task, used more learning strategies, and had more positive attitudes towards small group learning compared to students who worked with computers individually.