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Clark Quinn’s Learnings about Learning

Bad research

17 October 2023 by Clark 1 Comment

How do you know what’s dubious research? There are lots of signals, more than I can cover in one post. However, a recent discovery serves as an example to illustrate some useful signals. I was trying to recall a paper I recently read, which suggested that reading is better than video for comprehending issues. Whether that’s true or not isn’t the issue. What is the issue is that in my search, I came across an article that really violated a number of principles. As I am wont to do, let’s briefly talk about bad research.

The title of the article (paraphrasing) was “Research confirms that video is superior to text”. Sure, that could be the case! (Actually the results say, not surprisingly, that one media’s better for some things, and another’s better at other; BTW, one of our great translators of research to practice, Patti Shank, has a series of articles on video that’s worth paying attention to.) Still, this article claimed to have a definitive statement about at least one study. However, when I looked at it, there were several problems.

First, the study was a survey asking instructors what they thought of video. That’s not the same as an experimental study! A good study would choose some appropriate content, and then have equivalent versions in text and video, and then have a comprehension test. (BTW, these experiments have been done.) Asking opinions, even of experts, isn’t quite as good. And these weren’t experts, they were just a collection of instructors. They might have valid opinions, but their expertise wasn’t a basis for deciding.

Worse, the folks conducting the study had. a. video. platform.  Sorry, that’s not an unbiased observer. They have a vested interest in the outcome. What we want is an impartial evaluation. This simply couldn’t be it. Not least, the author was the CEO of the platform.

It got worse. There was also a citation of the unjustified claim that images are processed 60K times better than text, yet the source of that claim hasn’t been found! They also cited learning styles! Citing unjustified claims isn’t a good practice in sound research. (For instance, when reviewing articles, I used to recommend rejecting them if they talked learning styles.) Yes, it wasn’t a research article on it’s own, but…I think misleading folks isn’t justified in any article (unless it’s illustrative and you then correct the situation).

Look, you can find valuable insights in lots of unexpected places, and in lots of unexpected ways. (I talk about ‘business significance’ can be as useful as statistical significance.) However, an author with a vested interest, using an inappropriate method, to make claims that are supported by debunked data, isn’t it. Please, be careful out there!

Get the basics right first!

10 October 2023 by Clark Leave a Comment

I’m currently advising several organizations on their approaches to the use of technology to support learning. Moreover, I’ve been doing so for more than two decades, and see a lot more such situations as well. One of the things that I struggle with is seeing folks getting all agog over new technology, yet without getting the design right beforehand.  Thus, let me make a simple suggestion: get the basics right first!

So, we know what leads to good learning. Heck, I’ve written a book summarizing what’s known about it, and I’m not the only one. Despite that fact that humans are complex, and increasingly so are our learning goals, there exist robust principles. We know that we should provide a sufficient quantity of appropriately challenging contextualized practice with aligned feedback, for instance. That is, if we actually want to achieve an outcome.

Yet, too often, we don’t see this. We see, instead, information presentation. Sometimes even with a knowledge test! Yet, such an effort is unlikely to lead to any meaningful change. That is, the investment’s wasted!

Worse, too often we see this being done with fancy new tools. Sure, I get as attracted to shiny new objects as anyone. However, I want to understand their core affordances for learning. Anyone had the dubious pleasure of attending a slide presentation in a virtual world? Or maybe being presented with animated presentations of lots of facts? The new tools may have a short-term effect of novelty, but that’s it. The fundamental aspects of how our brains learn are what’s going to make, or break, a learning investment.

On the other hand, if we start with getting the learning right, first, then there may be additional value coming from the tech. Adaptivity, on top of quality learning design, can accelerate the outcomes.  Immersion, at the right time and place, is better than not. Language models, properly used, can have big impacts. However, it comes from knowing the specific capabilities, and matching them to the need.

While I haven’t done the ‘back of the envelope’ calculation (I’m not a financial whiz), I can state with a fair degree of comfort that you’re better off doing simple learning with good design. Bad design with shiny tech is still bad design! You’ll more likely have an impact putting your investment into learning quality than using fancy tech to deliver dreck. Of course, once you’ve done that, the investment in tech can do a lot more!

I’m not against new tech, heck I’ve written on games, mobile, and more! What I’m against is new tech in lieu of good design. And I’m even more enamored of good tech on top of good design.  So, get the basics right first, then add in the shiny objects. That way you’re going to have a good return on your $$, and that’s a good thing. Right?

PS, speaking of basics, we’ll be running a debate tomorrow (11 Oct) discussing the Learning Experience Design (LXD) label. I’m sure we’ll unpack critical issues. Check it out. 

Talking ‘transfer’

3 October 2023 by Clark Leave a Comment

I was looking to wrap up my slide deck for DevLearn (will be talking learning science), and wanted to see if there was anything missing. In particular, I knew I had a fair bit on retention, but I was checking on what I call ‘transfer’. In doing so, I realized that colleagues and others use the term differently! Which means it’s time to talk ‘transfer’.

So one of our good research translators is Will Thalheimer. I found his report (PDF) on transfer, and its usage was as many others I’d found. Will describes transfer as moving learning from the instructional environment to the workplace. No argument this is important! Yet, it’s not how I use the word.

In talking learning science, I’ve seen and said that the two gold standards are retention over time until needed, and transfer to all appropriate (and no inappropriate) situations. (That’s what I’ll be talking about in my session: what leads to those.) My notions here are both part of his transfer.

I get my usage of transfer essentially from folks like John Anderson at Carnegie Mellon Uni, who talks about what facilitates transfer. He’s the one I think of, for instance, when thinking of identical elements transfer, which stipulates that the more elements are the same, the higher the transfer. There’s near and far transfer, as well. That indicates the breadth of area you’re transferring to, really. E.g. negotiation would be far transfer, as there are many situations, whereas training to specifically run projector MX3600D4 is very much near transfer.

In a review of transfer I found (PDF), a distinction is made between ‘low-‘ and ‘high-road’ transfer. The former ‘happens’, while the latter is engineered. Given that, to me, instruction is about engineering success, maximizing likelihoods, I’m all for the latter. So, choosing contexts and supporting reflection.

To memory, even the academic literature about workplace learning seems to support the other interpretation. Yet, my term seems more in line with what the learning science community. In the longer term, we’ll need to reconcile, but for me, the distinction between the elements of retention and transfer are important. So, when I’m talking ‘transfer’, what I mean is the breadth of application. That’s my take, what are your thoughts?

Not diplomatic, but do care!

26 September 2023 by Clark Leave a Comment

So, I’ve been let know that my feedback is ‘blunt’. Which, I suppose, is better than some other alternatives. Still, I’d at least like to contextualize it, since I really can’t deny it. Hey, other people’s opinions are valid! They may not be correct, but I’m willing to acknowledge that it’s probably true. So, I guess I want to say I am not diplomatic, but do care.

So, I can be a little obtuse. I don’t always pick up on the subtleties of human interaction. Not a lot of evidence it’s actually worth a label, but… I recall going to meetings with my clients, who are executives at the C-level. We’d come out and they’d ask me “what did you see?” I’d respond with an analysis of the performance problem, and possible paths. I’d return the question, and hear things like “that’s the person with the real power”, “that one doesn’t like this other”, and other such perceptions. I just don’t see that stuff!

Even back when I was supervising students, I remember a couple of them saying “we never have any doubt about whether you’re not happy with something”. #oops On the other hand, I also typically don’t hear people saying I’m deceptive, or misleading. My opinions are pretty clear, but so too, generally, are my motives. (Because I’m inept at hiding them, I would suspect!) I do strive to make my feedback instructive as well as constructive. I perhaps over-err on the side of explaining why I’m saying something, and try to remember not to offer advice to fix it unless asked. (Not perfectly, by any means!)

I do also recognize that I may not always contextualize my feedback. In particular, I can forget to say what’s good before I say what should be fixed. I could defend myself and say that I don’t critique unless it’s worth fixing, but really I shouldn’t assume they know that. I am not deliberately mean, and never mean to hurt anyone’s feelings; I try to recognize that most folks don’t have bad intentions. And, of course, I don’t always succeed. Similarly, I try to admit my flaws, but again, don’t always succeed.

So, for the record, I care very much. And, we can be awesome! So, I do my best to share what I’ve learned. I freely admit my total luck at having opportunities to be the right place and have exposure to some great minds. I’ve had to work hard to learn it, mostly because it came easy early on. Then at the higher levels I learned that I couldn’t just wing it anymore.

So, my main point here is that when you see me critique things, it’s because it can be better. I do it publicly (though usually anonymously), so we can all learn. And I welcome feedback and pushback! I have lots to learn, and always will.

Oh, and please, please don’t be intimidated to talk to me. I’m really not an ogre. (I am a bit of an introvert, so I can seem standoffish, but it’s really just insecurity ;). Admittedly, I can have a very short fuse for folks trying to take advantage of me (or others), but… I really do care, and want to help everyone. I just have a responsibility to allocate my time in the most efficient ways. As I’ve said before, I talk ideas for free; I help someone personally for drinks/dinner; if someone’s making a quid, I deserve a cut. Until I hear otherwise, that’s seemed fair for close on two decades. So me: not diplomatic, but do care. Fair enough?

 

Modeling mental models

19 September 2023 by Clark Leave a Comment

I’ve talked in the past about mental models (and continue to do so), but they seem a difficult concept to grasp. I was discussing them again in preparation for this post by partner Elevator 9. Despite their utility, grounding in fundamental cognition, and value in learning, they continue to be absent or misunderstood in our learning interventions. It’s worth taking some time and modeling mental models in use.

feedback loopTo start with, what are mental models? Wikipedia defines them as “an internal representation of external reality”. Really, it’s an explanation of how a small part of the world works. Wikipedia goes on to add “the mind constructs ‘small-scale models’ of reality that it uses to anticipate events”. They can manifest as equations, or sets of rules, but really, to me, they’re constructed from causal conceptual relationships. That is, there are entities, connected by causality. For example, feedback loops are a mental model. They occur in many situations, and what happens is that something takes the output, and feeds it back to the input, positively or negatively, to influence subsequent actions.  For instance, a thermostat uses the temperature as a way to determine whether to turn on or off a heater or cooling device.

The next question is why mental models. Back to Wikipedia: they “can help shape behaviour and set an approach to solving problems”. To me, they’re explanatory and predictive, in that they can explain why something occurred, and predict the outcome of various actions. It’s that latter that provides the instructional value. We want people to make good decisions. If they have a basis for determining the outcome of different courses of action, they can choose the best one. Providing them with a model for the domain, e.g. interpersonal relations (c.f. situational leadership), gives learners a way to choose optimally.

There’s evidence that our brains will build models, and that they won’t necessarily be good ones. In addition, if we don’t have a good model, we try to patch it rather than replace it. Which isn’t necessarily effective. Thus, the best approach is to provide a good model up front, and demonstrate its use. Then we use examples to demonstrate models in context, showing how the abstract concepts map to real world elements. Further, in general, we provide them before we give practice in most cases.

Instructionally, then, providing models is good support for making decisions. I’ve argued before that making decisions is more likely to be the deciding value for organizations (as opposed to fact recall). Thus, instruction around making better decisions is important. Therefore, instruction using models is going to be valuable! As a relevant aside, in many cases they’re valuably communicated via diagrams or, in the case where dynamics are important for comprehension, via animation. The point is that as they’re conceptual, you save the photos or videos for the examples.

Finally, if models are useful, then they should be part of our instructional toolkit. One small problem is that subject matter experts have compiled their knowledge away, and may not have conscious access to the mental models they use. This makes it difficult to extract them and make them comprehensible to novices. Yet, clearly, they’re useful, so we should be doing that. Knowing what they are and why they’re useful is, hopefully, a motivator for making the effort. And, succeeding!

So, please, spend the effort. We should be modeling mental models to our learners. Find, refine, and present the models via examples. Then develop them through practice, and use them in feedback, explicitly. With models, we have a better basis for learning design, and better chances for successful improvement. Which is what it’s about, right?

Note: I talk about mental models in my book Learning Science for Instructional Designers.

 

Engaging people at work

12 September 2023 by Clark Leave a Comment

Last week, Donald Taylor wrote an interesting post, wondering about ‘learner engagement’. That’s a topic I do talk a wee bit about ;). He closed with a call for feedback. So, while I did comment there, I thought it potentially would benefit from a longer response. I think it’s more general than learner engagement, so I’m talking about engaging people at work. (But it’s still relevant to his thesis without quibbling about that!)

In his post, he talked about three levels: asset, culture, and environment. I’m not sure I quite follow (to me, culture is an environmental level), and I’ve talked about individual, team, and organizational levels. To his point, however, there are steps to take at every level.

He starts at the individual level, talking about designing learning experiences. I agree with his ‘do deeper analysis’ recommendation, but I’d go further. To me, it’s not just if they recognize that content’s valuable, it’s about building, and maintaining, motivation while controlling anxiety (c.f. Make It Meaningful!). I don’t think he’d disagree.

At the next level up, it’s about making sure people are connected. Here, I’d point to Self-Determination Theory (SDT), and ‘relatedness’. I don’t mind Dan Pink’s reinterpretation of that to ‘purpose’, in that I think people need to know how what they’re doing contributes to something bigger, and that something bigger supports society as a whole.

Finally, to me, is culture. You want a ‘learning organization‘, as Don agrees. He says to start with a sympathetic manager, but I think L&D needs to create that culture internally first, then take it to the broader organization (and starting with said manager is a good next step).

I think that latter step solves Don’s final step of breaking down barriers, but he’s a smart guy and I’m willing to believe I’m missing some nuance. I do like his focus on ‘find a measure’ to use. However, ultimately, it should improve a lot of measures around adapting to change: innovation, retention, and success.  That’s my take, I welcome yours!

To design is human

5 September 2023 by Clark Leave a Comment

I maintaining a fascination in design, for several reasons. As Herb Simon famously said: “The proper study of mankind is the science of design.” My take is to twist the title of Henry Petroski’s book, To Engineer is Human into ‘to design is human’. To me, design is both a fascinating study in cognition, and an area of application. The latter of which seems to be flourishing!

I’ve talked in the past about various design processes (and design overall, a lot). As we’ve moved from waterfall models like the original ADDIE, we’ve shifted to more iterative approaches. So, I’ve mentioned Michael Allen’s SAM, Megan Torrance’s LLAMA, etc.

And I’ve been hit with a few more! Just in the past few days I’ve seen LeaPS and EnABLE. They’re increasingly aware of important issues in learning science. All of this is, to me, good. Whether they’re just learning design approaches, or more performance consulting (that is, starting with a premise that a course may not be the answer), it’s good to think consciously about design.

My interest in design came in a roundabout way. As an undergrad, I designed my own major on Computer-Based Education, and then got a job designing and programming educational computer games. What that didn’t do, was teach me much about design as a practice. However, going back to grad school (for several reasons, including knowing that we didn’t have a good enough foundation for those game designs) got me steeped in cognition and design. Of course, what emerges is that they link at the wrists and ankles.

So, my lab was studying designing interfaces. This included understanding how we think, so as to design to match. My twist was to also design for how we learn. However, more implicitly than explicitly perhaps, was also the topic of how to design. Just as we have cognitive limitations as users, we have limitations as designers. Thus, we need to design our design processes, so as to minimize the errors our cognitive architecture will introduce.

Ultimately, what separates us from other creatures is our ability to create solutions to problems, to design. I know there’s now generative AI, but…it’s built on the average. I still think the superlative will come from people. Knowing when and how is important. Design is really what we want people to do, so it’s increasingly the focus of our learning designs. And it’s the process we use to create those solutions. Underpinning both is how we think, work, and learn.

To design is human, and so we need to understand humans to design optimally. Both for the process, and the product. This, I think, makes the case that we do need to understand our cognitive architecture in most everything we do. What do you think?

FWIW, I’ll be talking about the science of learning at DevLearn. Hope to see you there. 

Top 10 tools for Learning 2023

31 August 2023 by Clark 3 Comments

Somehow I missed colleague Jane Hart’s annual survey of top 10 tools for learning ’til just today, yet it’s the last day! I’ve participated in the past, and find it a valuable chance for reflection on my own, as well as seeing the results come out. So here’s my (belated) list of top 10 tools for learning 2023.

I’m using  Harold Jarche’s Personal Knowledge Mastery framework for learning here. His categories of seek (search and feed), sense (interpret) and share (closely or broadly) seems like an interesting and relevant way to organize my tools.

Seek

I subscribe to blog posts via email, and I use Feedblitz because I use it as a way for people to sign up for Learnlets. I finally started paying so they didn’t show gross ads (you can now signup safely; they lie when they say the have ‘brand-safe’ ads), and fortunately my mail removes images (for safety, unless I ask), so I don’t see them.

I’m also continuing to explore Mastodon (@quinnovator@sfba.social). It has its problems (e.g. hard to find others, smaller overall population), but I do find the conversations to be richer.

I’m similarly experimenting with Discord. It’s a place where I can generally communicate with colleagues.

I’m using Slack as a way to stay in touch, and I regularly learn from it, too. Like the previous two, it’s both seek and share, of course.

Of course, web surfing is still a regular activity. I’ve been using DuckDuckGo as a search engine instead of more famous ones, as I like the privacy policies better.

Sense

I still use Graffle as a diagramming tool (Mac only). Though I’m intrigued to try Apple’s FreeForm, in recent cases I’ve been editing old diagrams to update, and it’s hard to switch.

Apple’s Keynote is also still my ‘goto’ presentation maker, e.g. for my LDA activities. I have to occasionally use or output to Powerpoint, but for me, it’s a more elegant tool.

I also continue to use Microsoft’s Word as a writing tool. I’ve messed with Apple’s Pages, but…it doesn’t transfer over, and some colleagues need Word. Plus, that outlining is still critical.

Share

My blog (e.g. what you’re reading ;) is still my best sharing tool, so WordPress remains a top learning tool.

LinkedIn has risen to replace Twitter (which I now minimize my use of, owing to the regressive policies that continue to emerge). It’s where I not only auto-post these screeds, but respond to others.

As a closing note, I know a lot of people are using generative AI tools as thinking partners. I’ve avoided that for several reasons. For one, it’s clear that they’ve used others’ work to build them, yet there’s no benefit to the folks whose work has been purloined. There are also mistakes.  Probably wrongly, but I still trust my brain first. So there’re my top 10 tools for learning 2023

Sloppy thinking?

29 August 2023 by Clark Leave a Comment

paint splatterOk, so I admit that I’m a bit of a pedant (and I hear you, saying “a bit?”). So, when I see categorizations, I should be more accepting of pragmatic approaches. Yet, I still get upset when I see same, when there are clear conceptual breakdowns that could be used instead. My hypothesis is that the good conceptual ones end up making the discriminations (eventually), with perhaps a bit more explanation needed, but…they don’t leave misconceptions as likely to occur. Thus, I’m not sure I’m happy with sloppy thinking.

One example comes from a textbook I’m reviewing. They’re talking about performance support, and differentiate between EPSS (electronic performance support systems), PSS (performance support systems), and MPSS (mobile performance support systems). First, wouldn’t you start with PSS as the beginning point? The definition used is online and offline. OK, so I can see EPSS as a subset of that. It’s only online, right? So why does it lead the list?

Then, MPSS is a separate category. Isn’t it a subset of EPSS? They note that it is, in fact, an EPSS on a mobile device. So it’s a subset of the first category. You’re going from the middle category to the broader and then to the narrower. That confounds a general trend to follow an order, increasing or decreasing, rather than apparently random. They do note that MPSS can do location-specific things, but that’s also a subset of doing contextually-based things. So, a wee bit facile, it seems to me.

Similarly, I’ve seen a categorization of game technologies, including having spreadsheet-based as a different category from branching. Yes, but spreadsheets are just a mechanism to implement a formal model. It can be in a spreadsheet, or code. Why does the implementation matter? Pragmatically, yes, it matters, but then have spreadsheets and code-implemented as subsets of programmed models. For that matter, you could have an analog implementation of the model!

These are fairly rigorous criteria, whereas all too often I’ll see a list of things (e.g. things you should/never do for X) that aren’t of the same type. Clearly, it’s a marketing person just aggregating a list of things, without a true understanding. I think it’s problematic, however. For one, it’s a missed opportunity to reflect important conceptual distinctions (can you tell I’ve been an educator?). For another, it might lead people to think that being scattershot is ok. Finally, it might undermine the actual development of important categorizations.

I’m willing to believe that, for practical reasons, people do need the pragmatic distinctions. I just feel that the conceptually clear ones can yield that, too. Yes, again, it may take a little more exposition, but isn’t educating folks part of the job too (e.g. good marketing is good customer education)? So, while I feel a wee bit of an old man yelling “get off my lawn”, this is the reason why I struggle with sloppy thinking. Am I off base?

We play as we practice

22 August 2023 by Clark 6 Comments

I”ve advocated, repeatedly, the importance of practice. Yet, too often, we still see an ‘event’-based model, where it’s one and done. Unfortunately, this doesn’t align with how our brains work! I was looking at one of Elevator 9‘s Liftology videos (caveat: I did the original scripting), where they mentioned ‘practice like we play’. I’d heard it before (in various incarnations), but this time it struck me that perhaps it’s the right vehicle to penetrate complacency about learning design. Should we emphasize “we play as we practice”?

The underlying phenomena is that we need lots of practice, for two reasons. For one, the ‘learning’ mechanism that strengthens our learning can only do so much before it needs sleep. If you want to truly develop a skill, sufficient practice, over time, is required. It’s like building muscle, or training for a sport; occasional practice isn’t sufficient. The right practice, repeated and improved over time, is necessary.

The other is that we are very context sensitive. That is, our consciousness is very much influenced by where and how things are happening. If you want to successfully generate transfer to many different situations (such as sales, or negotiation, or…things that happen in many different contexts with different people and different goals and…), you need sufficient practice across contexts. Our brain abstracts across the contexts seen to determine the space of transfer. Thus, we need widely varied practice to generate a generalized ability to do. 

Yet, too often, we see people getting it right ‘once’, and thinking that’s enough. It might be sufficient to tick a box, but it’s not sufficient to generate a new ability. The problem is, there’s a lot of pressure against this. Folks don’t want to take the time and money, they want to believe that new information will yield a behavior change, it’s just too hard!

So, I’m wondering if rethinking the messaging will help. If we emphasize that what we do is dependent on what we practice, maybe we can get away from the school mentality of ‘study, pass test, forget’. We want to get to the ‘practice practice practice to be good enough to play’ mentality.

I don’t know if “we play as we practice” is the best vehicle, or even one, but I’m kinda desperate, I guess. I’m very very tired of folks not getting that meaningful change requires sustained effort. And I’m really looking for a solution. It seems like this might tap into some useful mental frameworks. Can this help? If not, do you have a better solution? Please?

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