What Candy Crush can teach us about teaching

Candy Crush Saga is a ridiculously addictive puzzle game. People literally spend hours swiping candies into lines of three or more. It's success is linked to its simplicity, but also the challenges in mastering it (see here for a good discussion).

In teaching, we often want students to master skills that range from the simple to the complex. So, does Candy Crush have anything to offer us in terms of improving teaching practice? According to a new paper by Evangeline Marlos Varonis and Maria Evangeline Varonis (both from University of Akron), it does. The authors look at Candy Crush through the lens of Universal Design for Learning (UDL). I am quite partial to UDL, and students in my classes may recognise it as I use a certain flavour of UDL in my teaching (it is one of three major strategies I employ, alongside interactive teaching, and contingent scaffolding).

The authors offer a number of course design takeaways from their investigation of Candy Crush. Most apply mainly to online courses, but some have wider application (and sound very much like things I do in my classes), including:

Do not let learners get stuck. Individualize instruction by providing hints, automatic or manual, when activities are challenging...

Provide students with regular feedback on performance and the opportunity to earn easy, small bonuses on activities or assessments. It might give them the perk they need to continually do their best and remain active in the class...

Rather than creating “one-and-done” assessments, individualize the learning experience by creating multiple opportunities for students to succeed. Learners who do poorly on a once-only assessment may predict their final grade and give up. Giving them the opportunity to take an assessment again, or to drop a lowest grade, can motivate them to continue despite an initial failure. This encourages students to focus on mastery rather than grades.

Provide additional, optional resources or activities that are available to learners even if the next unit is not. Those who are motivated can continue while those who are not are not penalized for not engaging, and once again you are affording learners some control over their environment...

Real-life examples are rarely as clean as those in a textbook, and if learners are truly preparing themselves for the workforce and lifelong learning, then problem-solving that requires analysis of the situation and synthesis is great preparation for what is to follow. Instructors can introduce additional complexity by incorporating problem-based learning in the form of case studies or projects that require learners to apply theoretical concepts to practical real-world situations...

Present new concepts or skills sequentially, but constantly build on what learners have accomplished by presenting activities and assessments that require not only that they demonstrate knowledge but also that they can apply this knowledge creatively in novel situations.

Offer learners options (e.g. choose between these three essays; complete two of the five modules; select a film to review from this list) so they maintain a choice in the curriculum they are pursuing, ushering it forward as they personalize it. Having choices other than “do this and pass” or “don’t do this and fail” will motivate learners to actively participate in the learning process...

Provide surprises that delight and compel further exploration. Easy bonus questions on an assessment or extra credit points for completing all work up to a certain point on time can be a reward, as can be a one-off content topic that is of inherent interest even though it is not strictly part of the curriculum of the course.

Of course, none of this is startlingly new, but it does suggest that at least some of the teaching that we do in class can be effectively 'gamified' for online teaching and learning. Although, I don't see myself being replaced by Tiffi anytime soon.

[HT: Ruth Taylor]

Why girls should have fewer male friends in high school

There is plenty of research that suggests that having a higher share of female classmates increases academic performance, both for boys and girls (see for example this paper). However, the gender composition of networks of friends hasn't been considered as often. A paper in the latest issue of the American Economic Journal: Applied Economics (it's complimentary access at the moment, but here is an ungated earlier version just in case) by Andrew Hill (University of South Carolina), entitled "The girl next door: The effect of opposite gender friends on high school achievement" goes some way towards addressing this gap.

In the paper, Hill investigated the effect of the share of opposite gender friends within students' friendship networks (rather than the share of girls only). One problem with this sort of analysis is that students choose their friends, and parents choose the schools that their children attend. So, there is likely to be some selection bias involved - if you simply compared students with more opposite gender friends with students with fewer opposite gender friends, you can't tell if any differences you observe are because of the share of opposite gender friends, or because of the selection bias. Hill overcomes this selection problem using instrumental variables analysis (which I have earlier discussed here): he essentially finds some variable that is expected to be related to the proportion of opposite gender friends, but shouldn’t plausibly have a direct effect on academic outcomes, and uses that variable in the analysis. In this case, he uses as an instrument the proportion of opposite gender schoolmates in their close neighbourhoods. As he says:

Students with more opposite gender schoolmates in their close neighborhoods have more opposite gender school friends, and, given that the gender composition of schoolmates in a student’s neighborhood is essentially random, provides plausibly exogenous variation in the share of opposite gender friends from which a causal effect on the outcomes of interest can be estimated.

The hypothesis being tested is that having more opposite gender friends decreases academic performance, through two potential mechanisms:

First... individuals in class may distract or be distracted by opposite gender friends more than same gender friends, reducing the quality of classroom inputs for individuals with a greater share of opposite gender friends...

Second... higher shares of opposite gender friends may increase the returns to leisure and therefore increase the time spent socializing at the expense of studying.

So, opposite gender friends are hypothesised to be a distraction to both in-class learning and out-of-class studying time. Hill finds that:

...an increase in the share of opposite gender school friends reduces academic achievement... A standard deviation increase in the share of opposite gender friends causes a half standard deviation reduction in GPA scores.

That effect is relatively large - the standard deviation of GPA in his sample is 0.8 (on a four-point GPA scale). However, when disaggregating by gender he finds that the effect is only statistically significant for girls. In other words, having a higher share of opposite gender friends is bad for girls, but possibly not so for boys. However, there is one part of his results that I do not fully agree with:

Results also indicate that opposite gender friends increase the probability of the student being in a romantic relationship, which may have adverse effects on achievement.

He uses the same instrumental variable approach to investigate the effects of the share of opposite gender friends on the probability of having been in a relationship in the past 18 months. Unfortunately, the instrument is not as valid in this case, as there is a plausible direct relationship between the share of opposite gender classmates living in the close neighbourhood and the probability of being in a relationship. Increased opportunity for interaction with opposite gender classmates (as would occur if there are more of them in the neighbourhood) increases the chances of starting a relationship (for at least some students!). So, while the results are plausible they are not necessarily causal.

Anyway, that doesn't take away from the overall results of the paper, which is that it is better for girls to have a higher share of female friends (and a smaller share of male friends), in terms of academic performance at high school. Which adds to the argument for the advantage of single gender schools (at least for girls), or for introducing single gender classes within coed high schools.

Why study economics? AEA video edition...

A few weeks ago, the American Economics Association (AEA) released a new video entitled "A career in Economics... it's much more than you think", that shows the value of studying economics. From their press release:

The 9-minute film is aimed at prospective or first-year students who may be investigating economics as a career option but are unclear how broadly a degree in economics can be applied. 

The film makes effort to dispel entrenched misconceptions about who economists are and what they do. Economics can be broadly defined as the study of human behaviors aimed at finding solutions to help improve peoples' lives. Viewers are reminded that a degree in economics doesn't have to be about finance, banking, business, or government, . . . it can be useful to all individuals and can lead to many interesting and fulfilling career choices. 

The video features four individuals offering insights on how economics can be a tool for solving very human problems and they provide some interesting perspectives on how they chose economics as a career path. The film also helps raise awareness about the need for more diverse voices in the field of economics.

• Marcella Alsan, a physician of infectious disease, discusses why she needed to pursue a degree in economics to improve the lives of her patients.

• Randall Lewis, a research scientist at Google, uses economics and "big data" as tools to improve the functioning of markets.

• Britni Wilcher, a PhD student of economics, offers insight on some misconceptions about economists and factors influencing her career path decision.

• Peter Henry, dean at the NYU Stern School of Business, points to the true nature of economics and the importance of diverse voices informing the field.

Access the video at this link. Enjoy!

The only thing I would add is that there is value to studying economics even if you are not strong mathematically - the intuition that underlies the economic way of thinking is itself valuable, and important. Understanding economics helps you to evaluate choices and make better decisions. Which is of course why economics is in the core of business and commerce degrees, but I would argue economics is also highly valuable for students in other disciplines as well (as the story of Marcela in the video should demonstrate).

Read more:

• Why study economics? Even if you won't be an economist edition...
• Why study economics? PhD edition...
• Why study economics? It could make you rich...
• Why study economics? Sheepskin effects edition
• Why study economics? NZ graduate earnings edition
• Why study economics?

Inequality was similar, or higher, in ancient times than it is today

I'm really enjoying my study leave, because it's giving me the opportunity to catch up on reading some papers that have been sitting on my must-read-soon pile, in some cases for years. This paper (pdf), by Branko Milanovic (World Bank), Peter Lindert (University of California, Davis), and Jeffrey Williamson (Harvard), entitled "Measuring Ancient Inequality" is one example.

If you're interested in inequality, or interested in economic history, the paper is a good read and provides some interesting insights (which I note that the authors have followed up in some subsequent publications, which I might talk about in a later post). The authors use data from social tables for 14 societies spanning from Rome (14 C.E.) to British India (1947), and a combination of Gini measures of inequality along with two new measures they term the inequality possibility frontier and the inequality extraction ratio.

They find:

First, as measured by the Gini coefficient, income inequality in still-pre-industrial countries today is not very different from inequality in distant pre-industrial times. In addition, the variance between countries then and now is much greater than the variance in average inequality between then and now. Second, the extraction ratio – how much of potential inequality was converted into actual inequality – was significantly bigger then than now. We are persuaded that much more can be learned about inequality in the past and the present by looking at the extraction ratio rather than just at actual inequality...

Third, differences in lifetime survival rates between rich and poor countries and between rich and poor individuals within countries were much higher two centuries ago than they are now, and this served to make for greater lifetime inequality in the past. Fourth, unlike the findings regarding the evolution of the 20th century inequality in advanced economies, our ancient inequality sample does not reveal any significant correlation between the income share of the top 1 percent and overall inequality. Thus, an equally high Gini could and was achieved in two ways: in some societies, a high income share of the elite coexisted with a yawning gap between it and the rest of society, and small differences in income amongst the non-elite; in other societies, the very top of income pyramid was followed by only slightly less rich people and then further down toward something that resembled a middle class... 

The frequent claim that inequality promotes accumulation and growth does not get much support from history. On the contrary, great economic inequality has always been correlated with extreme concentration of political power, and that power has always been used to widen the income gaps through rent-seeking and rent-keeping, forces that demonstrably retard economic growth. 

In other words, inequality within societies was similar in the past to what it is today, even though incomes were much lower then. But when you take into account life expectancy, inequality is much lower now than in the past. Although I'm not sure that a long life in abject poverty is necessarily an improvement on a short life in abject poverty. The final point is important though - there is little support for the conjecture that inequality promotes growth, and the reverse is likely.