Tag Archives: Learning

Personalized e-learning is on its way and we should be prepared


Personalization

With the rise of digitalization has come the rise of digital personalization. Personalization has been existent for a couple of years now, in different kinds of industries, such as retail, cars and even perfumes (Randall, Terwiesch & Ulrich 2005). This means companies and researchers also already had quite some time to learn about both the benefits and the drawbacks of personalization. However, the drawbacks are harder to overcome nowadays, since the use of personalization has already been implemented on such a big, global, scale. Think, for instance, about privacy concerns that could have at least partly been prevented if legislation was set in place in time. However, we can all understand that it is hard to act upon potential drawbacks in advance if there is no prior experience whatsoever.

Nevertheless, it is always a good idea to be cautious and critical about upcoming trends such as personalization, before blindly implementing them without thinking about any potential consequences, either negative or positive. This means, foreseeing any potential drawbacks, as well as keeping in mind what you would like to reach as a goal by pursuing a trend such as personalization.

Personalized e-learning

Ashman et al. (2014) have presented a detailed discussion regarding personalization, but not in the field of, e.g., e-commerce, where it is already widely implemented, but rather in the field of e-learning. Personalization in e-learning is still in its beginning phase and therefore not yet widely implemented. Thus, the authors act in advance on warning e-learning providers and educational institutions on the potential drawbacks of the personalization of e-learning, including recommendations on how to overcome them, before it is too late. Especially since educational institutions are increasingly using such models as a way to gain as much as new students as possible, to increase their income, risking to lose their initial, most important goal out of sight: to enhance the quality of education. (Ashman et al. 2014)

But why is personalization of e-learning initially needed, then? The authors acknowledge where institutions’ interest in personalization of e-learning is coming from. E-learning is an upcoming trend on its own already to overcome the lack of time and resources to facilitate an increasing number of students globally. However, students might feel disenfranchised and their individual learning needs might become neglected by the use of e-learning. To overcome this issue, educational institutions are starting to implement the personalization of e-learning. However, then again, personalization comes with its setbacks.

Setbacks

The three main setbacks discussed by Ashman et al. (2014) are privacy concerns, serendipity issues and deskilling problems. The authors discuss these three setbacks in great detail. Privacy concerns is a recurring issue surrounding the topic of data gathering in general, which is also needed for personalization. Serendipity issues are about the reduced ability to learn and understand different beliefs, cultures and lifestyles, or to learn ‘out of your comfort zone’, as personalization leads to the targeted student to only be presented information that fits within his/her field of interest. Lastly, students can be deskilled in the sense that they do not learn how to critically assess and evaluate the information that they are given, as with personalization they are presented the results that most closely fit their needs, so they stop looking further very quickly. The authors emphasize, in order to overcome these issues, it is important to inform students about what and how data is gathered about them, and to give them the opportunity to control what information is presented to them. Additionally, they advise a clear and thorough understanding by e-learning providers and educational institutions of why personalization in e-learning is needed and what can be achieved by it, for which thorough experimentation is required.

In their paper, several universities, such as Harvard, St. Gallen and Ontario, are used as an example, from which data is analyzed very extensively by Google Analytics. Google Analytics tracks staff and students on the websites of the universities. This enhances the concern of privacy, as the user ID’s were visible.

Opportunities

Despite these discussed setbacks, the authors do see great value in personalized e-learning as “the system is genuinely able to interact with users, recognize when they need assistance and guide them to the appropriate information or educational activity” (Ashman et al., 2014). Unfortunately, the authors of this paper focus solely on education in well-established economies, which is only a small part of the world. It would be interesting to see the possibilities of personalized e-learning being enforced globally, and thus in poorer areas, too. Interestingly, founder of Facebook, Mark Zuckerberg, and his wife, are planning to donate 99% of their Facebook shares to invest in, amongst other things, personalized learning. He mentioned:

“Students around the world will be able to use personalized learning tools over the internet, even if they don’t live near good schools. Of course it will take more than technology to give everyone a fair start in life, but personalized learning can be one scalable way to give all children a better education and more equal opportunity.” (Strauss, 2015)

pexels-photo-267399.jpeg

Let’s see what the future holds for us and the upcoming generations regarding a transformation in education, not only in well-established, advanced countries, but also in countries limited in access to good education. Although the negative consequences should not be forgotten and be acted upon well in advance…

References

Ashman, H., Brailsford, T., Cristea, A. I., Sheng, Q. Z., Stewart, C., Toms, E. G., & Wade, V. (2014). The ethical and social implications of personalization technologies for e-learning. Information & Management, 51, pp. 819–832.

Randall, T., Terwiesch, C., & Ulrich, K.T. (2005). Principles for user design of customized products. California Management Review, 47(4), 68. Links to an external site.

Straus, V. (2015). A primer for Mark Zuckerberg on personalized learning — by Harvard’s Howard Gardner. The Washington Post. 

Skillshare: The Future Belongs to the Curious


This start-up built an alternative education system that’s poised to have a major impact on the learning landscape” (Tracy, 2017).

Skillshare, launched in April 2011 by Michael Karnjanaprakorn (Joyner, 2017), is an online learning platform where the world’s best experts teach world’s best skills. With Skillshare it is possible to learn and practice a skill by doing. You can learn a skill together with their community of over 2 million students and teachers and network with them. Classes and skills are taught by expert practitioners, which makes it possible for everybody to get unlimited access to over 14,000 classes in different categories, such as design, technology, entrepreneurship and many more (Skillshare, 2017). This start-up  uses the benefits from crowdsourcing. The crowd is used to teach other interested individuals a new skill, that are traditionally performed by a designated agent (Howe, 2006)

how-it-works

Learning should be as easy as listening to music at Spotify or watching your favorite movie on Netflix. Skillshare is really about learning by doing and every class is project-based as well. Students can create projects, alter them to the website and can get feedback from students all around the world (Skillshare, 2017). Thus, unlike other educational online platforms, you don’t need to have a Ph.D. to teach something valuable. And on the other hand, learning skills is for everyone universal accessible and relatively inexpensive. It is for everyone easy to become a lifelong learner.The mission of Skillshare is to close the professional skill gap and provide universal access to high-quality learning (Skillshare, 2017). They believe that there is a huge difference between education and learning. Skillshare empowers people to take a leap in their careers, improve their lives and pursue the work they love, by teaching skills online that are needed in tomorrow’s world. This mission directly shows the major strength of Skillshare and how they differentiate themselves from competitive education platforms. Skillshare allows everyone to sign up and teach a class. By doing this they want to provide universal access to high-quality learning.

explaoin

How it works

For the lifelong learner, Skillshare makes it possible to get universal access to high-quality learning and to learn anything they want to. They offer the possibility to watch classes, online and offline, on your own schedule, anytime and anywhere. Thus they make it possible to learn at your own pace. Furthermore, the classes are taught by an expert with experience in the field. These classes include video lessons that are relatively short with most lessons under one hour, written text. And with the project-based environment you really learn by doing and are able to share your project in the class to get feedback and collaborate with a large community (Skillshare Help, 2017). They offer their members the possibility to create projects and build a portfolio of their work. On the other hand, Skillshare makes it possible for everyone to share their knowledge in a particular field, as long as the class follows certain guidelines. The company has proven adept at acquiring experts to teach on their website (Bromwich, 2015).

Skillshare has a freemium model which allows users to access free classes, create projects and discussions within them. However, this model includes videos with advertisements. A premium model offers their users to get unlimited access to over 14,000 classes, watch them offline and ad-free (Skillshare Premium, 2017).

Efficiency criteria:

Skillshare is one of the leading educational platforms that offers everyone universal access to learn a new skill at an affordable price. The platform maximizes the joint profitability of both of the players involved (Carson et al., 1999). On one side, it is for individuals easy to reach a large audience and teach them a skill of their experience. They are not bounded by a physical location anymore and therefore can have a more efficient personal schedule. Additionally, they can earn a little to a lot.

On the other side, many individuals can learn and practice a new skill at an affordable price. At the same time, they can collaborate with a large community and get feedback from them, so that the wisdom of the crowd can be used.

Evaluating the institutional environment, the largest threat for Skillshare is that there are too many new teachers who don’t add value to the platform. However, because there are guidelines and requirements that should be met before a class can be created, this threat is limited.

Concluded, Skillshare is an online platform that offers universal access to high-quality learning at an affordable price.

References:

Bromwich, J. (2015) ‘Anyone Can Be a Teacher at Skillshare, an Online School, The New York Times, available online from: https://www.nytimes.com/2015/03/20/education/anyone-can-be-a-teacher-in-this-online-school.html?_r=0 [28 February 2017].

Carson, S. J., Devinney, T. M., Dowling, G. R., & John, G. (1999) ‘Understanding institutional designs within marketing value systems’, Journal of Marketing, 115-130.

Howe, J. (2006) ‘The rise of crowdsourcing’, Wired, 14 (6).

Joyner, A. (2017) Skillshare Takes On the Education Gap, available online from: http://www.inc.com/best-industries-2013/april-joyner/skillshare-education-gap.html [28 February 2017].

Tracy, A. (2017) Skillshare: Redesigning  Education for the Masses, available online from: http://www.inc.com/abigail-tracy/35-under-35-skillshare-online-education-platform.html [28 February 2017].

Skillshare (2017) Unlimited access to over 14,000 classes, available online from: https://www.skillshare.com/ [28 February 2017].

Skillshare Help (2017) How does Skillshare work?, available online from: https://help.skillshare.com/hc/en-us/articles/205208147-How-does-Skillshare-work- [28 February 2017].

Skillshare Premium (2017) Why Premium?, available online from: https://www.skillshare.com/premium [28 February 2017].

Consider it sold


Opendoor is a San Francisco based start-up that steps into the real estate business, trying to make this process as easy as possible for the sellers and buyers. They are basically an intermediary in the market that brings together buyers and sellers. They buy real estate for cash, fix it and sell it for a small premium.

Business Model and Value creation

Opendoor uses an algorithm to determine what price to offer to the people that want to sell their homes via Opedoor. This algorithm includes thousands of variables, including for example square footage, numbers of bedrooms etcetera. Furthermore, Opendoor uses questionnaires to determine the preferences of the buyers and sellers, incorporating this in their model. In this way, the customers are actually co-creating the houses that Opendoor fixes. In the future, Opendoor also wants to offer customer mortgages and home decorations. Overall, the value that Opendoor adds is providing a service that takes away the burden of the customer to buy or sell houses and using the preferences of the customers in this process.

Opendoor buys family homes built after 1960 in the price range of $125000-$500000. Opendoor makes the homeowner an offer and once he accepts, inspects the house and closes the deal in cash.  The company makes money by taking a service fee of 6%, similar to the standard real estate commission, plus an additional fee that varies with the riskiness of the transaction what brings the total charge to an average of 8%. It then makes fixes recommended by inspectors and tries to sell the homes for a small premium. Buyers can look at the property and they receive a 30-day guarantee that Opendoor will buy it back if they’re not satisfied. (Forbes Welcome, 2017) (Opendoor, 2017)

Efficiency criteria and risks

When we look at the efficiency of the value system of Opendoor, we can look at two criteria, the joint profitability and the feasibility of required reallocations. (Carson et al., 1999) Opendoor definitely offers joint profitability, because consumers can easily sell or buy their homes via the platform, and Opendoor can profit by making money from the fixed houses. The second criteria is more difficult because Opendoor solely depends on investors and loans and when they don’t make profits they cannot reallocate their assets to satisfy their investors. Next to that, trust issues are also important to take into account. Opendoor cannot see the homes before they make an offer an have to rely on trust. Finally, competitors will not be that happy with Opendoor and therefore legal aspects will be important to consider while expanding.

The business model depends on whether the algorithm is right or wrong. If it is right then Opendoor will earn money, however, if the price is lower, Opendoor will make a loss. Next to that Opendoor pays in cash and loans this money. It is dependent on investors and if they encounter a low in the market they have a problem. They did not face a crisis like the one in 2008. All in all, let’s keep a close watch at this company and see whether they will conquer the real estate market.

Bibliography

Carson, S. J., Devinney, T. M., Dowling, G. R., & John, G. (1999). Understanding institutional designs within marketing value systems. Journal of Marketing, 115-130.

Forbes Welcome. (2017). [online] Forbes.com. Available at: http://www.forbes.com/sites/amyfeldman/2016/11/30/home-shopping-networkers-opendoor-is-upending-the-way-americans-buy-and-sell-homes/ [Accessed 14 Feb. 2017].

Opendoor. (2017). [online] Opendoor.com. Available at: https://www.opendoor.com/about [Accessed 17 Feb. 2017].

Saarijärvi, H., Kannan, P. K., & Kuusela, H. (2013). Value co-creation: theoretical approaches and practical implications. European Business Review, 25(1), 6-19.

 

Man versus Machine: Deep learning and its applications


What do the stock market prediction, medical diagnosis, employee selection, electrical demand prediction and personalization all have in common? They are all labor intensive. But do they have to be?

Deep Learning (DL) could be – and to some extent already is – the answer to various human labor intensive tasks. Deep learning is a subsection of machine learning that “focuses on computational models for information representation that exhibit similar characteristics to that of the neocortex”. (Arel et al., 2010).

Continue reading Man versus Machine: Deep learning and its applications