This Wednesday I’m involved with an experiment and presentation that is seeking to test out some alternatives for lectures/presentations. As it happens, the last week has brought a couple of events that are (so far) helping the case for the experiment. These are described below.
And now for a word from our sponsors…
The aim of the experiment it to break out of the geographic limitations of participation in lectures/presentations. Anyone with a web browser can participate (a Twitter account and mobile phone will increase your ability to participate, but aren’t necessary). The more people who use these medium, the better. So you are invited.
I work at CQUniversity. The university has 4/5 regional campuses spread across a fairly broad geographic area. A significant number of courses are offered across all of those campuses. A common approach for some years has been for lectures for these courses to be given from one campus and broadcast across the other campuses via the Interactive System-wide Learning (ISL) system. Essentially a video-conference system with specially built rooms at each of the campuses.
This approach is becoming embedded into the operations of the institution. To such an extent that the ISL rooms are becoming a resourcing bottleneck. Apart from teaching, these rooms are also used for research presentations and meetings. It’s getting to the stage that trying to get these rooms during campus is simply impossible.
Originally, the experiment was scheduled to use one room on each of the campuses
On Friday I was told that we’ve been bumped from the Mackay room. Apparently someone senior needs the Mackay room for an ISL session that is more important than my experiment.
Normally, this would have meant Mackay staff would miss out on the live presentation. They’d have to rely on the recorded presentation.
Not now. Theoretically, they should be able to participate the same as people off campus. I’m actually happy about this, it gives me a practical story to tell about why this approach might be useful. It will be interesting to see what problems arise.
PollEverywhere Polls and results
Over the weekend, while avoiding work on the presentation I came across this post from Wes Fryer. It describes how they used PollEverywhere in a conference presentation. PollEverywhere is essentially a commercial version of Votapedia which I plan to use on Wednesday.
Some things I found interesting:
The graphs. The PollEverywhere graphs look much nicer than Votapedias (minor point).
A comment that students like this approach because it is a legitimate use of their mobile phones in class.
The idea that this type of experiment was an “a-ha” moment for some.
present and explore the Bureaucratic Model as a narrative that we must understand if we are to influence the direction of adult education.
The talk resonated with me as much of my current struggles/work is trying to make folk aware of a range of unstated assumptions that guide their thinking about learning and teaching within a university context. As Jay says, we have to understand those assumptions before we can think of influencing the future of learning and teaching – and somewhere in that, universities.
Since Jay’s talk I’ve come across and/or been reminded of a range of related work. Please feel free to add more here.
A number of his implications seek to remove many of the basic assumptions that underpin university operation (e.g. semesters, fixed exams). However, a number of them show connections with an existing orthodoxy (e.g. all PhD students will have 6 months training in L&T).
That’s one of the problems I have with visioning. Too often it excludes interesting possibilities because it is held back by the background, preferences, ideas and prejudices of the people doing the visioning. My preference would be to let it emerge through a institution/setting that is flexible, open and questioning. I think much more interesting things can emerge from that situation than can ever happen because of the visioning of experts.
That’s because, no matter who you are, you have unstated assumptions that define what you can think of. Often this is addressed by having lots of different people do the visioning, but too often such attempts use approaches that to quickly focus on a particular vision, closing out future possibilities.
The grammar of school
In this post I mentioned a 1995 article by Seymour Papert on Why school reform is impossible. In this article Papert draws on Tyack and Cuban’s (1995) idea of the “grammar of school”
The structure of School is so deeply rooted that one reacts to deviations from it as one would to a grammatically deviant utterance: Both feel wrong on a level deeper than one’s ability to formulate reasons. This phenomenon is related to “assimilation blindness” insofar as it refers to a mechanism of mental closure to foreign ideas. I would make the relation even closer by noting that when one is not paying careful attention, one often actually hear the deviant utterance as the “nearest” grammatical utterance a transformation that might bring drastic change in meaning.
This sounds very much like what is happening in Jay’s bureaucratic model.
The need for experiments
A lot of the current debate about the future of universities is built on the comparison with print media. i.e. look, newspapers are a long-running institution that are dieing. Look, Universities, they are a long-running institution, they must be dieing also.
Revolutions create a curious inversion of perception. In ordinary times, people who do no more than describe the world around them are seen as pragmatists, while those who imagine fabulous alternative futures are viewed as radicals. The last couple of decades haven’t been ordinary, however. Inside the papers, the pragmatists were the ones simply looking out the window and noticing that the real world was increasingly resembling the unthinkable scenario. These people were treated as if they were barking mad. Meanwhile the people spinning visions of popular walled gardens and enthusiastic micropayment adoption, visions unsupported by reality, were regarded not as charlatans but saviors.
He then draws on the development of the printing press to talk about revolutions
That is what real revolutions are like. The old stuff gets broken faster than the new stuff is put in its place. The importance of any given experiment isn’t apparent at the moment it appears; big changes stall, small changes spread. Even the revolutionaries can’t predict what will happen
Dede’s metaphors of learning
Lastly, the following recording is of talk by Professor Chris Dede and some metaphors of learning. It is the current underlying assumption of consistency in delivery of learning that underpins much of what universities are currently doing which is my biggest bugbear. It’s what is contributing to university learning and teaching approaching what Dede describes as “the worst of fast food”.
A couple of colleagues and I are trying to kickstart a little thing we call the Indicators project. We’ve developed a “tag line” for the project which sums up the core of the project.
Enabling comparisons of LMS usage across institutions, platforms and time
The project is seeking to enable different people at different institutions to analyse what is being done with their institutions learning management system (LMS, VLE, CMS) and compare and contrast it with what is happening at different institutions with different LMS.
To some extent this project is about improving the quality of the data available to decision makers (which we define to include students, teaching staff, support staff and management). In part this is about address the problem identified by David Wiley
The data that we, educators, gather and utilize is all but garbage.
But it’s not just about the data. While the data might be useful, it’s only going to be as useful as the people who are seeing it, using it and talking about it. David Warlick makes this point about what’s happening in schools at the moment
not to mention that the only people who can make much use of it are the data dudes that school systems have been hiring over the past few years.
Collecting data less valuable that connecting people” http://bit.ly/3SMJCT agree?
If it’s an either/or question, then I agree. But with the indicators project I see this as a both/and question. For me, the indicators project is/should be collecting data in order to connect people.
What follows is an attempt to map out an example.
The link between LMS activity and grades
There is an established pattern within the literature around data mining LMS usage logs. That pattern is essentially
the higher the grade, the greater the usage of the LMS
The order is reversible as I don’t think anyone has firmly established a causal link, it’s just a pattern. My belief (yet to be tested) is that is probably, mostly good students get good grades and do everything they can do to get good grades, including using the LMS.
With our early work on the indicators project we have found some evidence of this pattern. See the two following graphs (click on them to see bigger versions).
The X axis in both graphs is student final grade at our current institution. From best to worst the grades are high distinction (HD), distinction (D), credit (C), pass (P), and fail (F).
In the first graph the Y axis is the average number of hits on either the course website or the course discussion forum. Hopefully you can see the pattern, students with better grades average a higher number of hits.
In the next graph, the Y axis is the average number of posts (starting a discussion thread) and the average number of replies (responding to an existing discussion thread) in the course discussion forum. So far, the number of replies is always greater than the number of posts. As you can see, the pattern is still there, but it is somewhat less evident for replies.
Importance of staff participation
Fresen (2007) identified the level of interaction or facilitation by teaching staff as a critical success factor for web-supported learning. We though we would test this out using the data from the project by dividing courses up into categories based on the level of staff participation.
The previous two graphs are actually for the 678 courses (the high staff particiaption courses) for which teaching staff had greater than 3000 hits on the course website during the term. The following two graphs show the same data, but for the super-low staff participation courses (n=849). A super-low course is one where teaching staff had less than 100 hits on the course website during term.
What do you notice about the pattern between grade and LMS usage?
First, the hits on the course site and the course discussion forum
Now, the average number of posts and replies in the course discussion forum
For me, the pattern is not there. The HD students appear to have decided there’s no value on the course website and decided they need to rely upon themselves. They’ve still been able to get a HD in spite of the super low staff participation. More work needs to be done.
I’m also interested in what the students in these super low courses might be talking about and what networks they are forming. The SNAPP tool/work at Wollongong might be useful here.
How to bring people together
My fear is that this type of finding will be used to “bring people together” in a way that is liable to be more destructive than anything. i.e. something like this:
The data mining dweebs (I do recognise that this probably includes my colleagues and I) will bring it to the attention of university management. After all, at least at my institution it’s increasingly management that have access to the dashboards, not the academic staff.
The data mining dweebs and management will tell stories about these recalcitrant “super-low” academics and their silliness.
A policy will be formulated, probably as part of “minimum standards” (aka maximum requirements), that academics must average at least X (probably 3000 or more) hits on their course website in a term.
While the indicators project is a research project focused on trying to generate some data, we also have to give some thought and be vocal about how the data could be used appropriately. Here are some initial thoughts on some steps that might help:
Make it visible. To some extent making this information visible will get people talking. But that visibility can’t be limited to management or even teaching staff. All participants need to be able to see it. We need to give some thought about how to do this.
Make it collaborative. If we can encourage as many people as possible to be interested in examining this data, thinking about it and working on ways to harness it to improve practice, then perhaps we can move away from the blame game.
Be vocal and critical about the blame game. While publicising the project and the resulting data, we need to continuously, loudly and effectively criticise the silliness of the “blame game”/policy approach to responding to the findings.
Emphasise the incompleteness and limitation of the data. The type of indicators/data we gather through the LMS is limited and from some perspectives flawed. An average doesn’t mean a great deal. You can’t make decisions with a great deal of certainty solely on this data. You need to dig deeper, use other methods and look closer at the specifics to get a picture of the real diversity in approaches. There may be some cases where a super-low staff participation approach makes a lot of sense.
Fresen, J. (2007). A taxonomy of factors to promote quality web-supported learning. International Journal on E-Learning, 6(3), 351-362.
I’ve just been to a meeting with a strangely optimistic group of people who are trying to gather “real stories” about what is going on within an organisation through focus groups. They are attempting to present this information to senior management in an attempt to get them to understand what staff are experiencing, to indicate that something different might need to be done.
We we asked to suggest other things they could be doing. For quite some time I’ve wanted to apply some of the approaches of Dave Snowden to tasks like this. The following mp3 audio is an excerpt from this recording of Dave explaining the results of one approach they have used. I recommend the entire recording or any of the others that are there.
I’m reluctant to post this. It’s part of a pragmatic approach to figuring out where, as an Australian academic, I should try and target publications. It seeks to identify publications in the higher education and educational technology areas that would be “best”.
I’m well aware of the questionable aspects of this approach, but if this is the game…. Especially when your institution is starting to discuss definitions of research active staff – the implication being that if you aren’t research active you don’t get time to do research – that include requirements for fixed numbers of A and A* journals within a 3 year period.
My mitigation strategy against this type of pragmatism is that I am fairly open when it comes to my research. Much of it gets an airing here first. It’s not much, but better than nothing (or at least that’s what I keep telling myself).
For my immediate purposes, it looks like AJET is a good fit. A journal that is open access.
Work to do
Find out how much value is placed on the difference between A and A* journals.
Check the final lists from the government to see if rankings have changed.
What’s your suggestion?
What’s the “best” publication outlet?
I’m assuming that when it comes to writing a paper based on that research that the first step is to choose the outlet. Which journal or conference are you aiming the paper at? I think you need to answer this question as there is a part of the writing process that has to respond to the specifics of the outlet (e.g. address the theme of a conference etc.).
In answering this question, I can think of at least the following dimensions to consider:
Quality. There are two common strategies I’ve heard: top down or bottom up. Bottom up folk go for the “worst” journal based on the hope that their poor article will get accepted. The top down folk suggest starting at the top because you never know, you might get lucky, and if you don’t you will at least get good feedback to improve the paper. At this stage you prepare it for submission to outlet #2.
Fit. i.e. the one which best fits the topic or point of your paper. Which may be to visit Hawaii (conference) or might be a topic match (the paper “Gerbils preference in social software” might be a good fit for the journal “Studies in Gerbil Selection of Social Software”.
Speed of review. How quickly will the journal accept and publish your paper.
Openness. Are the papers published in a closed or open manner? Can you circulate copies? Is the journal an open access journals .
The rankings approach that is increasingly prevalent tends to suggest that “Quality” is the first choice. The following focuses on the quality dimension, however, in operation there needs to be an appropriate balance with the other factors.
How to judge the top quality publication?
The “top quality publication” dimension begs the question, “How do you know what is the top quality publication?”. In some disciplines this is a clear cut thing. You can’t be a researcher within a field without knowing. The trouble is that in some other fields, it’s not so clear. Especially if you’re new to the field.
Those wonderful folk in the Australian government, following the lead of their British colleagues, are making it easier for us poor Australian academics. As part of this work they are developing “discipline-specific tiered outlet rankings”. i.e. if you want to play the game, you follow their rankings – while trying to balance the other dimensions.
While the Oz government lists are still under development John Lamp is providing a nice interface to view the rankings as part of his broader site. There’s a but field of research method and a search. This is provided for two lists from the Australian Research Council – an early draft one and a more recent one. The recent one isn’t that integrated into the database – so the following information is a bit out of date, but it gives an indication.
In the following I’ve selected those journals of potentially most interest to me – I could be mistaken and have left some important ones out – but it’s a start. I’ve added a link to the journal home page and made some comments from my look at their online information.
My main interests are in educational technology within higher education, so that’s the focus. Suggestions and comments welcome.
One of the outstanding tasks I have, is to determine how much of a difference folk are making between A and A* journals.
5K to 10K words Copyright is assigned to Tyrrell Burgess Associates with a fee? to cover all rights. Author allowed to circulate with acknolwedgement This is interesting
HIGHER EDUCATION REVIEW is committed to a problem-based epistemology. In all countries there is an urgent need to formulate the problems of post school education, to propose alternative solutions and to test them. The policy and practice of governments and institutions require constant scrutiny. New policies and ideas are needed in all forms of post school education as new challenges arise.
I’ve hated the idea of the LMS for quite some time. I even had the chance to briefly lead a project looking at investigating how PLEs could be grown and used within a university, at least before the organisational restructure came. In its short life the project produced a symposium, a number of publications, various presentations and a little bit of software.
Due to the background I had some significant interest in the symposium being organised by George Siemens and Stephen Downes. However, due to other responsibilities, odd times (given my geographical location) for the elluminate presentations and the low speed of my home Internet connection I knew I was unlikely to actively engage. Some of these factors have already prevented my on-going engagement with CCK09.
I probably would have left it there, however, over the last 24 hours two separate folk have mentioned the symposium and almost/sort of guilted me into following up. The one thing I can do at the moment, due to a fitness kick involving a great deal of walking, is listen to mp3s. So, I wanted an easy way to get the mp3s. A podcast sounds ideal for my current practices.
Last night I did a quick google and found this page that seems to provide a collection of links to video and audio recordings of presentations associated with the CCK09 course. Including some mp3s from the presentations at the PLEs & PLNs symposium
Rather than download and play silly buggers with iTunes I decided to recreate an approach we used on our first “Web 2.0 course site”. Using del.icio.us the students and staff in the course could tag audio/video for inclusion in a podcast created by Feedburner.
This post is an attempt to capture some adhoc, over night thoughts about how the indicators project might move forward.
Currently the indicators project is an emerging research project at CQUniversity. There are currently three researchers involved and we’re all fairly new to this type of project. I’d characterise the project at being at the stage where we’ve laid a fair bit of the ground work, done some initial work, identified some interesting holes in the literature around analytics/LMS evaluation and made the observation that there is a lot of different ways to go.
The basic aim is to turn the data gathered in Learning Mangement Systems (LMS, aka CMS, VLEs) usage logs into something useful that can help students, teaching staff, support staff, management and researchers using/interested in e-learning make sense of what is going on so they can do something useful. We’re particularly interested in doing this in a way that enables comparisons between different institutions and different LMS.
A traditional approach to this problem would be big up front design (BUFD). The idea is that we spend – or at least report that we spent – lots of time in analysis of the data, requirements and the literature before designing the complete solution. The assumption is that, like gods, we can learn everything we will ever need to know during the analysis phase and that implementation is just a straight forward translation process.
Frankly, I think that approach works only in the most simplistic of cases, and generally not even then because people are far from gods. The indicators project is a research project. We’re aiming to learn new things.
For me this means that we have to adopt a more emergent, agile or ateleological approach. Lots of small steps where we are learning through doing something meaningful.
Release small patterns, release often
So, rather than attempt to design a complete LMS and institutional independent data schema and associated scripts to leverage that data, lets start small, focus on one or two interesting aspects, take them through to something final and then reflect. i.e. focus on a depth first approach, rather than a breadth first.
As part of this we should take the release early, release often approach. Going breadth first is going to take some time. Depth first we should be able to have something useful that we can release and share. That something will/should also be fairly easy for someone else to experiment with. This will be important if we want to encourage other folk, from other institutions to participate.
We should also aim to build on what we have already done and also build on what other people have done. I think that the impact on LMS usage by various external factors might be a good fit.
External factors and LMS usage
First, this is a line of work in which others published. Malikowski, Thompson & Theis (2006) investigate what effect class size, level of class and college in which a course was offered had on feature adoption (only class size had significant impact). Hornik et al (2008) have put courses into high and low paradigms and seen how this, plus the level of the course, has impacted on outcomes in web-based courses. There are some limitations of this work we might be able to fill. For example, Malikowski et al (2006) manually checked courses sites and because of this are limited to observations from a single term.
Second, we’ve already done some work in this area in our first paper. We
This sort of examination of external factors and their impact on LMS usage is useful as it helps identify areas of interest in terms of further research and also potential insights for course design. It’s also (IMHO) somewhat useful in its own right without any need for additional research. So it’s something relatively easy for us to do, but also should be fairly easy for others to experiment with.
Abstracting this work up a bit
The first step in examining this might be an attempt to abstract out the basic principles and components of this sort of work. If we can establish some sort of pattern/abstraction this can guide us in the type of work required and some sort of move towards a more rigorous process. The following is my initial attempt.
There have been two main approaches we’ve taken in the first paper:
Impacts on student performance.
Impacts on LMS feature adoption.
Impacts on student performance
An example is the impact of an instructional designer. The following graph compares the level of student participation mapped against final result between course designed with an instructional designer and all other courses.
In this type of example, we’ve tended to use three main components:
A measure of LMS usage. So far we have concentrated on
the average number of hits by the student on the course website and discussion forum; and
the average number of posts and replies by the student on the discussion forum
A measure of student performance. Limited to grade achieved in the course, at the moment.
A way to group students. This has been done on the basis of mode of delivery/type of student (i.e. a distance education student, an Australian on-campus student, an international student) or by different types of courses.
Having identified these three components we can actively search for alternatives. What alternatives to student performance might there be?
For example, in the paper we use Fresen’s (2007) taxonomy of factors to promote quality web-supported learning as a way to group students. For example, staff participation should promote quality, hence is there any difference in courses with differing levels of staff participation?
Are there other theoretical insights which could guide this work?
Impacts on LMS feature adoption
We’ve used the LMS independent framework for LMS features developed by Malikowski et al (2007) to examine to what level different features are used within courses. We’ve looked at this over time and between different LMS. The following shows the evolution of feature adoption over time within the Blackboard LMS used at CQU.
Under this model, the components could be described as:
Framework for grouping LMS features.
Definition of adoption.
A mixture of the two?
I wonder if there’s any value in using the level of feature adoption as another way of grouping courses to identify if there’s any connection with student outcome. e.g. do courses with just content distribution have different student outcomes/usage than courses with everything?
Some quick ideas:
Look at improving the abstraction and alternatives of the two abstractions above.
Look at focusing on developing some platform independent database schema to enable the cross-LMS and cross-institutional comparison of the above two abstractions. This would include:
the database scheme;
some scripts to convert various LMS logs into that database format;
some tools to automate interseting graphs.
Fresen, J. (2007). “A taxonomy of factors to promote quality web-supported learning.” International Journal on E-Learning 6(3): 351-362.
Hornik, S., C. S. Saunders, et al. (2008). “The impact of paradigm development and course level on performance in technology-mediated learning environments.” Informing Science 11: 35-58.
Malikowski, S., M. Thompson, et al. (2006). “External factors associated with adopting a CMS in resident college courses.” Internet and Higher Education 9(3): 163-174.
Malikowski, S., M. Thompson, et al. (2007). “A model for research into course management systems: bridging technology and learning theory.” Journal of Educational Computing Research 36(2): 149-173.
After at least a decade of “wouldn’t it be a good idea if” and at least one aborted attempt (hint: an organisational restructure in which you are a loser, is not a great context for a new project with intra-organisational implications), the Indicators Project is getting started. This post is my attempt to define what the project means for me. What I hope to get out of the project, and what I hope others might get out of the project.
The main aim is to let people know about the project and encourage feedback, either here or on the project blog.
The data that we, educators, gather and utilize is all but garbage. What passes for data for practicing educators? An aggregate score in a column in a gradebook. A massive, course-grained rolling up of dozens or hundreds of items into a single, collapsed, almost meaningless score. “Test 2: 87.” What teacher maintains item-level data for the exams they give? What teacher keeps this data semester to semester, year-to year? What teacher ever goes back and reviews this historical data?
For a long time I have believed that the absence and/or poor quality of the data available has meant that universities have been particularly bad at sensemaking around learning and teaching, and especially e-learning.
For me, a major consequence of this “garbage data” is that decisions made within universities (I work within a university, I’m paid to help improve learning and teaching at that institution, so my focus is on universities) about learning and teaching, and especially about e-learning, are made with very little sense of what is happening within the real world. This situation is increasingly getting worse as, at least within my experience, management at universities are attempting to adopt a more top-down, “corporate” approach to decision making.
Such an approach to decision making means that when management make the decisions about learning and teaching not only don’t have good data to base their decision on. They are also making decisions on the basis of one of the following categories of teaching experience:
only taught recently with a significant amount of support; (this means they don’t have to experience all the low level “make work” that consumes so much time)
haven’t taught for a number of years;
have never taught within the local context; or
have never taught.
For individual academics, they are stuck with the “garbage data” from their own courses and their own gut feel. Since teaching at University is mostly a solo activity, there is little or no opportunity to compare and contrast with the experience of others. Even when the opportunity does arise, it has to be done with “garbage data”.
Support staff, be they instructional designers, academic developers or IT folk, are almost entirely without data, which means they can’t target their assistance. They have to take a one size fits all (i.e. one size that helps no-one) approach. Mainly because what data that is available about learning and teaching is only available to the teacher or their line supervisor.
Students, well they are at the bottom of the pile. They get essentially no indication of how where the sit with respect to other students. etc.
The indicators project aims to provide better data to teaching staff, management, support staff and students.
using technology to capture, manage, and visualize educational data in support of teacher decision making has the potential to vastly improve the effectiveness of education.
A lot of the work by Dave Snowden is based around the idea of achieving
A synthesis of technology and human intelligence
Using technology for what it is good for in order to generate indicators that can help people do what they are good at – pattern matching.
David Wiley’s long term goal is huge, difficult and expensive. You can read more about it on his blog. That goal is beyond the scope of our little indicators project. I think the aims for our project can be summarised as:
Identify potentially interesting indicators from LMS usage data and some other institutional data (e.g. student characteristics etc.).
Make that information available to students, teaching staff, management, support staff and researchers. We aren’t likely to achieve all this at once, different folk will get it at different times.
Engage in additional research around the indicators, how they are used, how they can be used and what they can tell us about learning and teaching.
Return to step #1.
Cross platform and cross institution
Importantly, we’re aiming to/hoping for the project to identify, encourage and enable use of the indicators across different institutions and different LMS. As we progress, we’ll be looking for people interest in partnering with the project.
In an attempt to understand what we have to do and where the interesting work might be we developed the following graphical representation of the project.
Working from the bottom up, the figure includes:
LMS and institutional specific data. Each institution will have its own LMS and also some other data in the form of information about the students (e.g. age, country of origin, type of student) and the courses (e.g. discipline, number of campuses offered at etc.).
We need to do some “research” to identify the knowledge necessary to effectively convert this institutional and LMS dependent data into something that is independent of LMS and institution.
The LMS & institutional independent data forms the main data source of the indicators. At the very least, partner institutions will be able to perform comparisons. In a perfect world, the data will be in such a form as to enable free sharing, anyone who has an interest can get the data and perform analysis.
We then need to do some research to generate knowledge to convert the LMS and institution independent data into indicators. The indicators abstract the data into a form that provides useful knowledge for students, teachers, managers, support staff or researchers. One simple example, is the percentage of courses within an LMS that have adopted specific features.
Some of the “useful knowledge” will be passed onto the institutional business intelligence folk who are responsible for institutional data warehouses, dashboards and the like.
Some of the useful knowledge will be used by a variety of people (teaching staff, support staff, students and management) to improve the practice of learning and teaching.
Some of the useful knowledge will be used as the basis for additional research to identify the whys and wherefores of the indicators. For example, Why do international students “break” the link between LMS activity and student grades?
This is by no means a simple task. There are any number of problems that will impact the project. Here are some.
Online only is rare
David Wiley is in the somewhat rare situation of having an online only context
The Open High School of Utah is the first context in which I’m studying this use of technology. Because it is an online high school, every interaction students have with content (the order in which they view resources, the time they spend viewing them, the things they skip, etc.) and every interaction they have with assessments (the time they spend answering them, their success in answering them, etc.) can all be captured and leveraged to support teachers.
It is very rare for my institution, and I’m assuming many other universities, to have courses that are entirely online. In our situation a large percentage of our students must attend on-campus sessions and another large percentage believes they are missing out on something important if they don’t get face-to-face. So, in our situation the online data is only ever going to tell part of the story. It is going to have to be supplemented with other approaches and methods.
David Warlick in a blog post that responds to David Wiley’s post (is it me, or are there a lot of David’s in this post?) identifies the problems with data quality
even in the best of situations, the data is scarce, shallow, grainy, and awfully expensive to collect
He is perhaps talking about a different context with high schools, but some of these limitations apply in existing work. Much of the research into LMS usage has focused on the use of surveys, interviews of manual examination of course sites to generate insight. Where data mining is done on system data it is often for limited time frames (e.g. 1 term or 1 year) and is usually communicated in a LMS dependent way that makes comparisons between systems and institutions difficult.
not to mention that the only people who can make much use of it are the data dudes that school systems have been hiring over the past few years.
This is a problem I’ve seen with universities with the rise of data warehouses and dashboard. Unless there is a particular motivated and well resourced team, such information systems become the toys of the “data dudes”, occasionally the weapons of managers who wish to make a particular point, or a resource for a small group of researchers to publish papers. They rarely become embedded into the day to day practice of learning and teaching.
The LMS problem
The LMS is based on the assumption that all “learning” – or at least content access and discussion forum use – occurs within the LMS. This “one ring to rule them all” approach does provide one benefit. All of this data is in the one place, the one system, the one database.
This “one ring to rule them all” approach is also, in my opinion and that of many others, the main problem with the LMS. It removes choice from the student and the teacher about what tools can be used. However, if alternatives such as personal learning environments become prevalent, then the sort of approach being adopted by the indicators project will no longer be possible. The focus will have to change to the type of question Stephen Downes raised when pointing to Wiley’s post
Shouldn’t we be devising ways for students to organize and track their own learning?
This an important point. If I had my way we wouldn’t be using an LMS. The trouble is that the LMS is the almost universal response to e-learning by universities. To get them to change, we’re going to have to – at the very least – provide lots of meaningful data that encourage management and others to recognise the limitations of the LMS approach. Certainly one of my aims in being involved with the indicators project is to illustrate the inherent limitations and problems with the LMS approach.
Where to from here?
The project is starting to gather some momentum. We’ve had our first paper accepted at a conference. We’re talking about research and ALTC grants. We’ve started identifying additional work we need to make progress on, in particular making a start on the cross LMS comparisons. We’re talking about making connections with various folk to help the project move one.
So, feel free to share your comments and thoughts.
The aim of this post is to investigate the question of whether or not the learning pyramid (see following figure – click to expand) is true or false, or perhaps a hoax, myth, misdirection, useful model and/or theory based on verifiable research.
In the end, I confirm my belief that it is a hoax/myth. I don’t believe it is useful in guiding the design of learning and teaching, in fact, I believe it to be destructive. It aims to provide a simplistic and wrong basis on which to guide design, when such design should be guided by and engage with a recognition that teaching is complex, difficult and contextual and can’t be improved by silver bullets
What do you think? (I do recognise that my direct opposition in the last paragraph is likely to significantly limit alternate perspectives, but I though I’d best be clear of my view given the prevalence of the figure.)
They put up a pyramid I quite liked that had retention rates for lectures at 5% at the top through to teaching others as 90% effective for retaining information (see book, p. 19) and suggested assessments should be aimed at the bottom half of the triangle (discussion activities, practice by doing, teaching others).
This sounds an awful lot like the above pyramid.
Quite some time ago I came across this post by Will Thalheimer. The post essentially seeks to argue that the pyramid is not based on any published research and suffers from a number of major flaws. I was convinced by this post and have since taken the view that the pyramid is false/a myth. I believed this to the extent that when another colleague used the learning pyramid in a blog post, I posted a comment linking back to the naysayer post by Thalheimer.
I was going to post a similar response to Wendy’s post but couldn’t remember some of the resources, so I revisited my comment on Scott’s post. To my surprise, I discovered that Scott had responded to my comment. The surprise arose both from the fact that I don’t remember receiving a notification of the reply (though that may say more about my memory than the technology); and that Scott was claiming that the learning pyramid was based on research that addressed some of the problems. i.e. that there was some basis. In addition, Scott suggests that the questions raised about the pyramid may arise from folk with questionable motives and also suggests that the naysayers don’t provide evidence or experimental research.
I’m going to spend a bit of time seeing what I can find about this difference of perspective. Is the pyramid based on some research? Have I been basing my dismissal of the pyramid on work by people with an axe to grind? Is there evidence to suggest that the pyramid is wrong?
Origins of the pyramid
One obvious place to start is to find out whether the proposed research actually exists. Does the research institute that is supposed to have done this research exist?
Lalley and Miller (2007) claim
No specific credible research was uncovered to support the pyramid, which is loosely associated with the theory proposed by the well-respected researcher, Edgar Dale. Dale is credited with creating the Cone of Experience in 1946.
This is from the abstract of their paper displayed on this ERIC page. My institution’s library doesn’t have access to the full text in electronic form, I’m chasing up a paper copy. (Of course the library website is currently down so I can’t log a request to get a copy of the paper…). Annoyingly, the institution I’m doing my PhD through has digital access to the journal, but not for 2006 through 2008.
Further web research has found a copy of the Lalley and Miller (2007) paper online here. The aim of this article is
Therefore, it is our intention to examine the following: the source of the general structure of the pyramid, Dale’s Cone of Experience; available research on retention from the methods identified by the pyramid; and consider the relationship(s) among the methods.
Rather than Bell Laboratories being the source of research, the research is generally referenced back to the National Training Laboratories in Bethel Maine. From information on the web it appears that this organisation is now known as the NTL Institute. Lalley and Miller (2007) quote from a response from the NTL Institute to a query about the pyramid
Institute at our Bethel, Maine campus in the early sixties when we were still part of the National Education Association’s Adult Education Division. Yes, we believe it to be accurate–but no, we no longer have–nor can we find–the original research that supports the numbers. We get many inquiries every month about this–and many, many people have searched for the original research and have come up empty handed. We know that in 1954 a similar pyramid with slightly different numbers appeared on p. 43 of a book called Audio-Visual Methods in Teaching, published by the Edgar Dale Dryden Press in New York. Yet the Learning Pyramid as such seems to have been modified and always has been attributed to NTL Institute.
Lalley and Miller (2007) go onto give some arguments about why it is appears questionable that this research was ever/could ever be done.
The origins and data for the pyramid look very questionable. So, is there data or research to suggest that the pyramid is wrong?
What’s the literature say?
Lalley and Miller (2007) then go onto review the literature about each of the different methods of instruction included in they pyramid. The aim being to find out what the literature says about retention rates. I have not read all of what they have written (I have a thesis to get back to), but in summary they say (emphasis added)
The research reviewed here demonstrates that use of each of the methods identified by the pyramid resulted in retention, with none being consistently superior to the others and all being effective in certain contexts.
Lalley and Miller’s (2007) final conclusion is that direction instruction, such as a lecture, remains very important as a part of the mix of approaches required. They close the article with
Not surprisingly, this returns us to the assertions of Dale (1946) and Dewey (1916) that for successful learning experiences, students need to experience a variety of instructional methods and that direct instruction needs to be accompanied by methods that further student understanding and recognize why what they are learning is useful.
Rutger van de Sande from a University in the Netherlands has blog post that connects with this myth. He supervised some students (physics teachers) in an experiment to test retention. The rationale and results are explained on this knol. In a small scale study, likely to have all sorts of limitations, they established different percentages to the pyramid, which they conclude “to be an all too simplistic model”.
This, admittedly small, collection of research (though Lalley and Miller draw on a significant body of research) seems to provide evidence and experimental research to disprove the ideas of the pyramid.
Axe to grind?
Do the folk questioning the pyramid have an axe to grind? That’s a difficult question to answer without significant knowledge of who they are. So, let’s start with the question of who they are.
Rutger van de Sande – an “experience educational researcher and teacher educator”. Looks like a keen academic trying to make his way in the world.
Will Thalheimer – consultant and researcher Okay, a consultant, which potentially means there’s some potential benefit in getting more people to his site (which has ads). Attacking a broadly accepted idea is a good way to attract attention. Given the challenge to the effectiveness of learning styles, you could argue that there is a trend developing here. (I should note that academics in search of citations have the same motivation)
Don’t think these guys form a cabal aimed at attacking the legitimacy of an ideas based on sound empirical research. You could argue that the attention given by attacking such a widely accepted idea might be motivation, but the data seems to suggest that the pyramid is based on questionable to non-existent data.
Why does this continue to get air play?
A number of the folk who have written about this pyramid or commented on blogs about it have asked the question “Why does it continue to get air play?”. I have a preference for two explanations:
“looking for a silver bullet, a simplistic approach to a complex issue” (Metiri Group, 2008) Teaching and learning is a wicked problem, especially in some of the increasingly diverse contexts people are facing. For some/many folk it’s easier to believe in a simple, universal solution than engage in the full complexity of the problem. This is, I suggest, encouraged to extreme ends in the increasingly “corporate world” of higher education.
Confirmation bias – “an irrational tendency to search for, interpret or remember information in a way that confirms preconceptions or working hypotheses. i.e. a lot of education folk don’t like lectures. A lot of education folk have a barrow to push in terms of problem-based learning, discovery learning, authentic learning…..etc. The pyramid confirms the biases these folk have and hence they are more ready to accept than critique.
I don’t like the way most lectures are given, they are very poor. I like even less that most of the focus of many courses is on giving lectures. But I don’t believe there’s a silver bullet.
Of course, the idea that I don’t believe there is a silver bullet – i.e. I don’t the application authentic learning will save a course, a program, an institution or the world – means that I have a confirmation bias that leans towards thinking the learning pyramid is a hoax.
Lalley, J. and R. Miller (2007). “The learning pyramid: Does it point teachers in the right direction?” Education and Information Technologies 128(1): 64-79.
Metiri Group (2008). Multimodal learning through media: What the research says, Cisco Systems: 24.
eportfolios are a vast hidden overhead. They really only make sense if they are portable and accessible to the user. Transferring vast quantities of student held data out of the university every spring seems complicated. Better, maybe, to instruct students to use external services.
But that’s not the point of this post. This morning Dave tweeted for folk to respond to a comment on the post by Diego Leal on strategic plans for educational technology in universities.
Strategic plans in educational technology are a bugbear of mine. I’ve been writing and thinking about them a lot recently. So I’ve bitten.
My starting position is that I’m strongly against strategic plans for educational technology in organisations. However, I’m enough of a pragmatist to recognise that – for various reasons (mostly political) – organisations have to have them. If they must have them, they must be very light on specifics and focus on enabling learning and improvement.
My main reason for this is a belief that strategic plans generally embody an assumption about organisations and planning that simply doesn’t exist within universities, especially in the context of educational technology. This mismatch results in strategic plans generally creating or enabling problems.
Important: I don’t believe that the problems with strategic plans (for edtech in higher education) arise because they are implemented badly. I believe problems with strategic plans arise because they are completely inappropriate for edtech in higher education. Strategic plans might work for other purposes, but not this one.
This mismatch leads to the following (amongst others) common problems:
Purpose proxies (Introna, 1996); i.e. rather than measure good learning and teaching, an institution measures how many people are using the LMS or have a graduate certificate in learning and teaching.
Suboptimal stable equilibria (March, 1991)
Technology gravity (McDonald & Gibbons, 2009)
Introna (1996) identified three necessary conditions for the type of process embedded in a strategic plan to be possible. They are:
The behaviour of the system is relatively stable and predictable.
The planners are able to manipulate system behaviour.
The planners are able to accurately determine goals or criteria for success.
In a recent talk I argued that none of those conditions exist within the practice of learning and teaching in higher education. It’s a point I also argue in a section of my thesis
The talk includes some discussion of some principles of a different approach to the same problem. That alternative is based on the idea of ateleological design suggested by Introna (1996). An idea that is very similar to broader debates in various other areas of research. This section of my thesis describes the two ends of the process spectrum.
It is my position that educational technology in higher education – due to its diversity and rapid pace of change – has to be much further towards the ateleological, emergent, naturalistic or exploitation end of the spectrum.
Statement of biases
I’ve only ever worked at the one institution (for coming up to 20 years) and have been significantly influenced by that experience. Experience which has included spending 6 months developing a strategic plan for Information Technology in Learning and Teaching that was approved by the Academic Board of the institution, used by the IT Division to justify a range of budget claims, thrown out/forgotten, and now, about 5 years later, many of the recommendations are being actioned. The experience also includes spending 7 or so years developing an e-learning system from the bottom up, in spite of the organisational hierarchy.
So I am perhaps not the most objective voice.
Argyris, C., R. Putnam, et al. (1985). Action science: Concepts, methods and skills for research and intervention. San Francisco, Jossey-Bass.
Birnbaum, R. (2000). Management Fads in Higher Education: Where They Come From, What They Do, Why They Fail. San Francisco, Jossey-Bass.
Introna, L. (1996). “Notes on ateleological information systems development.” Information Technology & People 9(4): 20-39.
March, J. (1991). “Exploration and exploitation in organizational learning.” Organization Science 2(1): 71-87.
McDonald, J. and A. Gibbons (2009). “Technology I, II, and III: criteria for understanding and improving the practice of instructional technology ” Educational Technology Research and Development 57(3): 377-392.
Swanson, E. B. and N. C. Ramiller (2004). “Innovating mindfully with information technology.” MIS Quarterly 28(4): 553-583.