Genetic Algorithms in Education

In online education, there a variety of interactive group activities categorized as collaborative learning. Discussion forums is one such example of a collaborative learning strategy, group/partner project work is another. Where group dynamics play a more significant role in the learning process than other types of teaching methods, getting the right mixture of students together can have a significant effect on learning outcomes [1].
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Student performance and moral decision making in predictive technologies

Pattern recognition is a well established technique utilized by neural networks in applications that attempt to make predictions on human behaviour within a limited context. ‘Many successful researchers have used Neural Network and Decision Trees in the subject of prediction and decision making’1. In the field of education, the future behaviour of a student can be said to be important to know in order to illicit an intervention, pre-emptively by the teacher or administration. ‘Predictive’ profiling is understood to be ‘identifying who an individual is, classifying what they are and evaluating what they might be’2. In [1], the proposed modelling approach includes a feed forward network (to predict future student performance results with past data) and an additional recurrent network that maps the current state of the student’s performance to a future desired state so that an intervention, or a decision can be made. In 3, a traditional feed forward NN was used to analyze learning behaviour (represented as data collected by a web-based system), to ‘classify students according to their usual performance and finally to predict their final grades’. The utilization of the NN technique improved classification which elevated the accuracy rate of the model to reach 89.96%.
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Computational Intelligence


The problem that CI is trying to solve is to how to create an intelligent system. As a  partial answer to the question ‘what is intelligence’, CI looks to nature for inspiration and tries to mimic, through algorithms, a degree of that observable intelligence 1.  If one definition of intelligence includes making a decision in the face of  uncertainty, or making inferences based on past experiences, then with some confidence we can say that process resembles ‘intelligence’. The end result is a program that can generate decisions more like a human or animal. The reason this is desirable is because there are certain problems that can be better solved by nature, like how to evolve, how to self-organize, or for a predator, how to spot the weakest in the herd. Whether or not we want computers to be better at spotting the weakest in the heard is a good question, but the difference between how computers and humans process information makes it a challenging problem to implement.  To deal with that challenge, there is a group of nature-inspired algorithms: Fuzzy logic, evolutionary computation, neural networks (also swarm optimization and genetic algorithms) — together these research fields make up what is known to be CI. 2

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Protecting privacy

Personal information is gold

Companies makes billions from it, governments and criminals go to great lengths to get it, store and analyze it. The real-world consequences for an individual who loses control of that data are identity theft, fraud, blackmail, surveillance and potential threats to personal safety and property.

The value of privacy

Most businesses require some personal information in order to function. As a contractor I have built websites for lawyers, real estate agents, restaurants, fitness companies and artists who rely on me to create information systems that meet their legal obligations for the province in which they reside.

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Machine Learning

I had some time to myself recently so I was able to do things that I like — like…thinking about machine learning? No, really. I like thinking about that. What started off as tinkering, puttering, and being mildly spontaneous led to following up on some of my own curiosities. Freeing myself even briefly from my predictable, repetitive life is satisfying enough but I found myself falling into watching documentaries and movies that no one that I share a household with would ever tolerate.

In two days, with the help of a cold and a house-sitting stint, I’ve watched:

The narratives of these movies provided a broad context within which I could re-think about programming. The questions they raise are interesting. In my day to day life for example, programming  has a very narrow context, that is, programming in an educational context is still very much focused on finding efficiencies in workflow. No objection to that. It can be fun and at least it’s useful. I also don’t kid myself by assuming that it’s particularly ground breaking, at least from a computing perspective. Automating repetitive tasks has been a stable delivery of computing since its inception and distributing educational materials broadly, in different formats, or through different media channels is not a hot research topic. An area that is notable, in the very least that it’s hard to not to see the money flowing towards it is finding answers to questions around how machines (but really by this we mean programs) help us learn. Machine learning, adaptive learning, artificial intelligence are different terms used to describe what is essentially programming.

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Pressbooks plugin developed by BCcampus enables truly open textbook publishing

BCcampus has around 70 open textbooks in its collection, and more are being added each day. Once more textbooks are added (following the next phase of the project: 20 skills and trades textbooks), the sustainability of the collection will become more important. That means building technology that allows for the “Five Rs” of openness: reuse, revise, remix, redistribute, and retain.

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Three tricks to writing a tech story for non-developers

At BCcampus, we’re all about technology. Our boilerplate is: “We are an educational technology organization ensuring B.C. learners, educators, and administrators get the best, most effective technologies and services for their learning and teaching needs.”

Nevertheless, the main audience for the corporate web site consists of educators, administrators, instructional designers, librarians, and ministry officials. Not necessarily technologists, and certainly they all are people who don’t have the time to delve into the finer points of software development in a blog post. In-depth articles are therefore not normally part of our content marketing strategy.
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