<p>The MCPL literature suggests that for an FI to directly improve learning, rather than motivate learning, it has to help the recipient to <em>reject erroneous hypotheses.</em> Whereas correcting errors is a feature of some types of FI messages, most types of FI messages do not contain such information and therefore should not improve learning—a claim consistent with CAI research.</p> <p>Moreover, even in learning situations where performance seems to benefit from FIs, learning through <em>FIs may be inferior to learning through discovery</em> (learning based on feedback from the task, rather than on feedback from an external agent). Task feedback may force the participant to learn task rules and recognize errors (e.g., Frese &amp; Zapf, 1994), whereas FI may lead the participant to learn how to use the FI as a crutch, while shortcutting the need for task learning (cf. J. R. Anderson, 1987). </p>

In the MCPL literature, several reviewers doubt whether FIs have any learning value (Balzer et al., 1989; Brehmer, 1980) and suggest alternatives to FI for increasing learning, such as providing the learner with more task information (Balzer et al., 1989). Another alternative to an FI is designing work or learning<br> environments that encourage trial and error, thus maximizing learning from task feedback without a direct intervention (Frese &amp; Zapf, 1994).

Those teachers who keep a list of question prompts relating to the various levels of Bloom’s Taxonomy undoubtedly do a better job of encouraging higher-order thinking in their students than those who have no such tool. On the other hand, as anyone who has worked with a group of educators to classify a group of questions and learning activities according to the Taxonomy can attest, there is little consensus about what seemingly self-evident terms like “analysis,” or “evaluation” mean. In addition, so many worthwhile activities, such as authentic problems and projects, cannot be mapped to the Taxonomy, and trying to do that would diminish their potential as learning opportunities.

The categories or “levels” of Bloom’s taxonomy (knowledge, comprehension, application, analysis, synthesis, and evaluation) are not supported by any research on learning. The only distinction that is supported by research is the distinction between declarative/conceptual knowledge (which enables recall, comprehension, or understanding) and procedural knowledge (which enables application or task performance).

The problem with calling it “lurking” makes everyone think negative thoughts. Like our community is full of Peeping Tom’s or other people with nefarious intent. People who don’t talk <strong>are</strong> still participating and learning – just in some non-obvious ways.

Lurking als Lernen: <em>“Lurking is not a problem, as long as lurkers are learning because enough material is created and shared by nonlurkers.”</em> <a href="http://etcjournal.com/2011/04/19/connectivism/" target="_blank">(Claude Almansi)</a>

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.

<div class="para"><p>The claim that there is a distinctive new generation of students in possession of sophisticated technology skills and with learning preferences for which education is not equipped to support has excited much recent attention. Proponents arguing that education must change dramatically to cater for the needs of these digital natives have sparked an academic form of a ‘moral panic’ using extreme arguments that have lacked empirical evidence.</p></div><div class="para"><p>The picture beginning to emerge from research on young people's relationships with technology is much more complex than the digital native characterisation suggests. While technology is embedded in their lives, young people's use and skills are not uniform. There is no evidence of widespread and universal disaffection, or of a distinctly different learning style the like of which has never been seen before. </p></div>

<p><strong><span style="text-decoration: underline;">1. Class Size</span></strong></p> <p><span style="text-decoration: underline;">My initial thought:</span> Decreasing Class Size from 25 to 15 could significantly improve student achievement.</p> <p><span style="text-decoration: underline;">The bold, loud claim I hear:</span>&nbsp; “Decreasing class sizes is a key to student success!”</p> <p><span style="text-decoration: underline;">What the research says:</span>&nbsp; Of the 138 factors of the meta-analyses done, this was ranked as number 106, and had a impact factor of 0.21, well below the hinge point of showing notable change.&nbsp; This is based on studies of more than 40000 classes, and nearly 950000 students worldwide. Perhaps not surprisingly, “quality teaching” has nearly double the impact on student achievement than this factor.</p> <p><span style="text-decoration: underline;">My new thought:</span><strong>&nbsp; </strong>Not the high-yield strategy that I believed.</p>

<p><strong><span style="text-decoration: underline;">6.&nbsp; Formative Evaluation of programs</span></strong></p> <p><span style="text-decoration: underline;">My initial thought</span>:&nbsp; Extremely important for teachers to adapt and change their methodologies in response to student learning. Using student data to guide instruction and reflection through collaboration with their peers is something that we have been<a href="http://thelearningnation.blogspot.com/2010/11/restructuring-not-remortgaging-to-make.html"> focussing on in our school through our change in structures</a>.</p> <p><span style="text-decoration: underline;">Loud, bold claim I hear:</span>&nbsp; “I know what works in my class!”</p> <p><span style="text-decoration: underline;">What the research says</span>:&nbsp; This ranks as #3 of 138, with an effect of 0.9 over nearly 4000 students and 38 studies.&nbsp; Teachers being purposeful to innovations in that they are looking to see “what works” and “why it works” as well as looking for reasons why students do not do well lead to improvement in instruction and student achievement.</p> <p><span style="text-decoration: underline;">My new thought</span>:&nbsp; This is the high-yield strategy that can really make a difference at our school, and through the Professional Learning Community Model of providing time for teachers to collaborate and reflect on teaching practices, we have seen a marked increase in the success of our students.</p>

<b>Conclusion </b> Spaced education consisting of clinical scenarios and questions distributed weekly via e-mail can significantly improve students' retention of medical knowledge.

The Modified Low-First Method is an optimal spaced learning method which was derived from a reactivation theory of spacing effects and was designed to be effective by setting as advantageous spaces as possible for all items and for any learners with various working memory capacities. It consists of three principles; the first is to sort all items by their probabilities of recall in ascending order at the end of each learning session for the subsequent session, and the second is to omit items whose probabilities of recall have reached a certain level, and the third is to transit to a new learning session when the number of unrecalled items in a session have reached a certain number.

Spaced learning usually leads to better recognition memory as compared with massed learning, yet the underlying neural mechanisms remain elusive.

Recognition memory tests afterward revealed a significant spacing effect: Participants recognized more items learnt under the spaced learning condition than under the massed learning condition.

<em>Purpose</em> – <it>The purpose of this paper is to compare the impact of a long-term (13-week, spaced learning) with a short-term (two-day, block intensive) coaching skills training programme on participants' coaching skills and emotional intelligence.</it>

<em>Findings</em> – <it>Participation in the 13-week training course was associated with increases in both goal-focused coaching skills and emotional intelligence, whereas the two-day block intensive training was associated with increased goal-focused coaching skills, but not emotional intelligence. Further, the magnitude of the increase in goal-focused coaching skills was less for the two-day programme than for the 13-week programme.</it>

On-line spaced education can generate improvements in learning that are retained 2 years later. Although the effect size is modest, the persistence of detectable knowledge differences between educational interventions after such a long duration is exceedingly unusual.

In other words, get the learner into a task quickly, and then provide content instruction through the feedback.

Numerous contradictions of cognitive load theory’s predictions have been found, but with germane cognitive load, they can still be explained away.&nbsp; de Jong does not use this term (unfalsifiable) but instead states that germane cognitive load is a <em>post-hoc</em> explanation with no theoretical basis: “there seems to be no grounds for asserting that processes that lead to (correct) schema acquisition will impose a higher cognitive load than learning processes that do not lead to (correct) schemas” (2009).

2. <span style="text-decoration: underline;">Poor external validity of lab-based studies</span>.&nbsp; Moreno doesn’t touch on something in the de Jong article – the fact that most cognitive load (and multimedia learning) studies are conducted in labs that “includes participants who have no specific interest in learning the domain involved and who are also given a very short study time” (de Jong, 2009), often only a few minutes.&nbsp; Quite a number of findings from these studies have not held up as strongly when tested in classrooms or real-world scenarios, or have even reversed (<a href="http://www.txwes.edu/professionaldevelopment/materials/Multimedia%20Instructions.pdf">such as the modality effect</a>, but see <a href="http://dx.doi.org/10.1016/j.learninstruc.2007.09.010">this refutation</a> and this <a href="http://cat.inist.fr/?aModele=afficheN&amp;cpsidt=5135499">other example of a reverse effect</a>).