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Student Version

A teacher is one who guides or leads. To guide does not necessarily mean to instruct directly. We often think of teaching as direct instruction (presenting information, asking questions, giving feedback, demonstrating some procedure, evaluating student progress, and so on). But a teacher can guide without instructing directly. A good example is the Montessori system of education. In a Montessori school, most of what a child learns is through interacting with a variety of curriculum materials in a particular context. A Montessori teacher does much less direct instruction than do teachers in traditional schools.

References:
Frick, T. (1991). Restructuring education through technology. Bloomington, IN: Phi Delta Kappa Educational Foundation.

Teachers should be guides or leaders. In the role of a guide, a teacher does less presenting of information, demonstrating and providing feedback. For example, in a Montessori school, most student learning occurs through interaction with a variety of class materials, rather than interaction with a teacher.

Original Source Material

Student Version

To summarize, the elaboration model of instruction starts by presenting knowledge at a very general or simplified level in the form of a special kind of overview. Then it proceeds toadd detail or complexity in "layers" across the entire breadth of the content of the course (or curriculum), one layer at a time, until the desired level of detail or complexity is reached.

References:
Reigeluth, C. M. (1999). The elaboration theory: Guidance for scope and sequence decisions. In C. M. Reigeluth (Ed.), Instructional design theories and models: A new paradigm of instructional theory(Vol. II, pp. 425-453). Hillsdale, NJ: Lawrence Erlbaum.

They soon switched to a model based on the elaboration theory (Reigeluth, 1999). Using this approach, the game would begin with a level that offered the simplest version of the whole task (the epitome); subsequent levels would become increasingly more complex--an approach common to videogames--with opportunities for review and synthesis.

References:
Reigeluth, C. M. (1999). The elaboration theory: Guidance for scope and sequence decisions. In C. M. Reigeluth (Ed.), Instructional design theories and models: A new paradigm of instructional theory(Vol. II, pp. 425-453). Hillsdale, NJ: Lawrence Erlbaum.

Original Source Material

Student Version

In a complex task such as creating a website for learning, instructors may want to support the generation of multiple solutions in learners' peer feedback. Anonymity may create a social context where learners feel freer to express varied ideas, and make the task of giving feedback less inhibited. However, teachers need to know just how anonymity impacts the learning dynamic in order to make informed choices about when anonymous configurations are appropriate in peer feedback.

References:
Howard, C. D., Barrett, A. F., & Frick, T. W. (2010). Anonymity to promote peer feedback: Pre-service teachers' comments in asynchronous computer-mediated communication. Journal of Educational Computing Research, 43(1), 89-112.

Increased availability of technology in my classroom makes it easier for peer feedback activities to be conducted anonymously which "may create a social context where learners feel freer to express varied ideas, and make the task of giving feedback less inhibited" (Howard, Barrett, & Frick, 2010, p. 90). However, I worry that my students may be overly harsh if they don't have to stand by their comments.

References:
Howard, C. D., Barrett, A. F., & Frick, T. W. (2010). Anonymity to promote peer feedback: Pre-service teachers' comments in asynchronous computer-mediated communication. Journal of Educational Computing Research, 43(1), 89-112.

Original Source Material

Student Version

While solitary negative reactions or unjustified suggestions for change have the potential to dissipate discourse rather than build it, the pattern analysis shows that the anonymous condition seemed to provide a safe explorative space for learners to try out more reasons for their multiple solutions. Teachers will rarely give anonymous feedback, but the experience of giving anonymous feedback may open a social space where learners can try out the reasons for their suggestions.

References:
Howard, C. D., Barrett, A. F., & Frick, T. W. (2010). Anonymity to promote peer feedback: Pre-service teachers' comments in asynchronous computer-mediated communication. Journal of Educational Computing Research, 43(1), 89-112.

In their study of anonymity in an online peer feedback activity, the authors found that, under conditions of anonymity, learners seemed more inclined to provide reasons to back up their suggestions (Howard, Barrett, & Frick, 2010). Getting both suggestions and the reasons for the suggestions would be welcome in feedback I receive from peers or my instructors. Seeing the reasons would help me know that the suggestions have been thought through (even if I don't always agree with them).

References:
Howard, C. D., Barrett, A. F., & Frick, T. W. (2010). Anonymity to promote peer feedback: Pre-service teachers' comments in asynchronous computer-mediated communication. Journal of Educational Computing Research, 43(1), 89-112.

Original Source Material

Student Version

The concept of systems is really quite simple. The basic idea is that a system has parts that fit together to make a whole; but where it gets complicated - and interesting - is how those parts are connected or related to each other. There are many kinds of systems: government systems, health systems, military systems, business systems, and educational systems, to name a few.

References:
Frick, T. (1991). Restructuring education through technology. Bloomington, IN: Phi Delta Kappa Educational Foundation. Retrieved from https://www.indiana.edu/~tedfrick/
fastback/fastback326.html#nature

Frick (1991) claims that systems, including both business systems, and educational systems, are actually very simple. The main idea is that systems "have parts that fit together to make a whole" (The nature of systems in education section, para. 1). What is further interesting to Frick is how those parts are connected together.

References:
Frick, T. (1991). Restructuring education through technology. Bloomington, IN: Phi Delta Kappa Educational Foundation. Retrieved from https://www.indiana.edu/~tedfrick/
fastback/fastback326.html#nature

Original Source Material

Student Version

Instructional designers typically employ models to guide their day-to-day work. Due to the increased practice of the systematic design of instruction in a growing number of settings, available models become more and more proliferated, focusing on particular types and contexts of learning, particular groups of learners or designers, or particular instructional units (either whole curricula or individual modules or lessons.)

The main goal of any instructional design process is to construct a learning environment in order to provide learners with the conditions that support desired learning processes.

References:
Merriënboer, J. J. van. (1997). Training complex cognitive skills. Englewood Cliffs, NJ: Educational Technology Publications.

"The main goal of any instructional design process is to construct a learning environment in order to provide learners with the conditions that support desired learning processes" (van Merriënboer, 1997, p. 2). Process models proliferate because more and more designers generate models that focus on specific contexts, learners, or even units of instruction, according to van Merriënboer.

References:
Merriënboer, J. J. van. (1997). Training complex cognitive skills. Englewood Cliffs, NJ: Educational Technology Publications.

Original Source Material

Student Version

Analysis of patterns in time (APT) is a method for gathering information about observable phenomena such that probabilities of temporal patterns of events can be estimated empirically. If appropriate sampling strategies are employed, temporal patterns can be predicted from APT results. Finally, APT is compared to the linear models approach and event history analysis. The major difference is that in APT there is no mathematical model assumed to characterize relations among variables. In APT the model is the temporal pattern being investigated.

References:
Frick, T. (1990). Analysis of Patterns in Time (APT): A Method of Recording and Quantifying Temporal Relations in Education. American Educational Research Journal, 27(1), 180-204.

APT is an empirical approach to observing and coding phenomena by using mutually exclusive and exhaustive categories within multiple classifications (Frick, 1990). Once these data have been collected, researchers specify APT queries to calculate the probability of joint and/or sequential patterns of interest. In effect, researchers create measures of temporal patterns by counting the occurrences of these coded patterns. According to Frick, Analysis of Patterns in Time is different from the linear models approach of measuring variables separately and using statistics to analyze their relations.

References:
Frick, T. (1990). Analysis of Patterns in Time (APT): A Method of Recording and Quantifying Temporal Relations in Education. American Educational Research Journal, 27(1), 180-204.

Original Source Material

Student Version

Because computer systems exhibit performative intelligence, we can teach them to do tasks. It is this very capability that makes it possible to use computers as an interactive medium for instruction and learning. It is interaction which sets computers systems apart from other media such as books, television, and film. However, present-day computers literally do not understand the culturally bound meanings of the messages which they manipulate during these interactions because such computers lack qualitative intelligence.

References:
Frick, T. (1997). Artificially intelligent tutoring systems: what computers can and can't know. Journal of Educational Computing Research, 16(2), 107-124.

According to Frick (1997), computer systems demonstrate performative intelligence, when compared to other media such as books, television, and film. Computers can be programmed to do things. This feature of computer systems makes them an alternative medium for instruction and learning. However, he claims that computer systems lack the ability to understand the meaning of messages they send and receive during interaction with students and teachers.

References:
Frick, T. (1997). Artificially intelligent tutoring systems: what computers can and can't know. Journal of Educational Computing Research, 16(2), 107-124.

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Student Version

Educational researchers, policymakers, and practitioners agree that educational research is often divorced from the problems and issues of everyday practice--a split that creates a need for new research approaches that speak directly to problems of practice (National Research Council [NRC], 2002) and that lead to the development of "usable knowledge" (Lagemann, 2002). Design-based research (Brown, 1992; Collins, 1992) is an emerging paradigm for the study of learning in context through the systematic design and study of instructional strategies and tools. We argue that design-based research can help create and extend knowledge about developing, enacting, and sustaining innovative learning environments.

References:
DBRC (Design-Based Research Collective). (2003). Design-based research: An emerging paradigm for educational inquiry. Educational Researcher, 32(1), 5-8.

A decade later, researchers interested in studying learning in naturalistic settings (inspired by Brown's approach) began a concerted effort to define the standards and argue the legitimacy of this type of research through design. For example, the Design-Based Research Collective defined design-based research (DBR) as "an emerging paradigm for the study of learning in context, through the systematic design and study of instructional strategies and tools" (DBRC, 2003, p. 5).

References:
DBRC (Design-Based Research Collective). (2003). Design-based research: An emerging paradigm for educational inquiry. Educational Researcher, 32(1), 5-8.

Original Source Material

Student Version

First, the potential of digital games is discussed using the tutor/tool/tutee framework proposed by Taylor (1980). Second, the potential of digital games to enhance learning by connecting game worlds and real worlds is stated. Third, the possibility of digital games to facilitate collaborative problem-solving is addressed. Fourth, the capability of digital games to provide an affective environment for science learning is suggested. Last, the potential of using digital games to promote science learning for younger students is indicated.

References:
Li, M. C., & Tsai, C. C. (2013). Game-Based Learning in Science Education: A Review of Relevant Research. Journal of Science Education and Technology, 1-22.

There are five advantages of using games in science learning stated in the literature. Games can be used as tools; make connections between virtual worlds and the real world; promote collaborative problem solving; provide affective and safe environments; and encourage younger students for science learning.