Thus Kirschner, Sweller and Clark's paper is an important reminder for us to not carry Problem Based Learning (PBL) to its extreme. That is, while it has its strengths, learners often need a more direct approach in order to build a solid foundations before being presented with PBL.

With the title blaring, “<em>Why Minimal Guidance during Instruction Does Not Work”</em> rather than, <em>“Why Minimal Guidance during Instruction Does Not Work for Novice Learners,” </em>the authors almost seem to ignore that PBL is a necessity in order to promote deeper levels of understanding.

The paper relies heavily on Cognitive Load Theory, yet we have to realize that it is still a theory rather than a law.

Thus, both the authors and the constructivism movement are guilty of jumping on theories before they are fully understood.

Connectivism is the application of network principles to define both knowledge and the process of learning. Knowledge is defined as a particular pattern of relationships and learning is defined as the creation of new connections and patterns as well as the ability to maneuver around existing networks/patterns.

Results showed that, while instructional designers apparently do make use of process-based ID models, they do not spend the majority of their time working with them nor do they follow them in a rigid fashion. They also engage in a wide variety of other tasks that are not reflected in ID models.

Rowland (1992) reported his results to be congruent with the research on expertise and indicated that expert instructional designers clearly employ a definable problem solving and decision-making process. He suggested that ID tools, unlike procedural design models, should foster a deep understanding of the system of concern and should include such characteristics as flexibility of structures and processes, a workspace for construction of problem representation, and mechanisms for making multiple links between problems and solutions. Rowland suggested that, rather than to be taught procedures or even problem-solving heuristics, novices need to develop experience in the design process and that a case-based method of teaching, providing involvement with real or realistic situations, might be the most appropriate way for new instructional designers to learn the design process.

Design is always about making judgments about design situations that are complex, rich and replete with tensions and contradictions.

<span class="blsp-spelling-error" id="SPELLING_ERROR_30">Kirshner</span> argues, very clearly, that non-<span class="blsp-spelling-error" id="SPELLING_ERROR_31">instructivist</span> methods result in no better learning than direct instruction, and sometimes in *less* learning, because of the 'cognitive overhead' required in self-directed methodologies.<br><br><span class="blsp-spelling-error" id="SPELLING_ERROR_32">Kirshner's</span> argument on this point is not based on experimental data, but rather, on his theory of cognition. Specifically, he argues that short-term memory has a limited capacity, and that if some of this capacity is not available for new facts (because it is taken up 'selecting scientific principles') then the transfer of information to the student is reduced.<br><br>I respond to <span class="blsp-spelling-error" id="SPELLING_ERROR_33">this</span> argument by showing how <span class="blsp-spelling-error" id="SPELLING_ERROR_34">Kirshner's</span> theory is false. We do not 'retrieve theories' into short term memory and then 'select' from them. That is not how thinking works; that is not ow scientific thinking works. And therefore, <span class="blsp-spelling-error" id="SPELLING_ERROR_35">Kirshner's</span> argument, on these grounds, against student-directed learning, fails.

The best mechanism for demonstrating knowledge is not likely the production of a certain set of facts on demand. Expertise in a discipline on the <span class="blsp-spelling-error" id="SPELLING_ERROR_54">part</span> of a student is something that is typically *recognized*, not measured, by people who are already experts in the field.