Category Archives: Education

It seems to be a recurring theme  on Freakonomics. This new NBER working paper by economists Scott E. Carrell and Bruce Sacerdote deals with the idea of educational incentives. They found that even those incentives that are offered to students late in their senior year of high school, can impact college outcomes, but not if it’s only money given and the impact is not the same for all students , as you already can discover in the abstract (you can download the paper here):

We present evidence from an ongoing field experiment in college coaching/ mentoring. The experiment is designed to ask whether mentoring plus cash incentives provided to high school students late in their senior year have meaningful impacts on college going and persistence. For women, we find large impacts on the decision to enroll in college and to remain in college. Intention to treat estimates are an increase in 15 percentage points in the college going rate (against a base rate of 50 percent) while treatment on the treated estimates are 30 percentage points. Offering cash bonuses alone without mentoring has no effect. There are no effects for men in the sample. The absence of effects for men is not explained by an interaction of the program with academic ability, work habits, or family and guidance support for college applications. However, differential returns to college and/or occupational choice may explain some of the differences in treatment effects for men and women.

We already know for some time the cognitive theory of multimedia learning by Mayer. These new findings somewhat fits with this theory as a new research by Jennifer Kaminski and Vladimir Sloutsky from Ohio State. They found that adding captivating visuals to a textbook lesson to attract children’s interest may sometimes make it harder for them to learn, as they found that 6- to 8-year-old children best learned how to read simple bar graphs when the graphs were plain and a single color.

From the press release:

“Graphs with pictures may be more visually appealing and engaging to children than those without pictures. However, engagement in the task does not guarantee that children are focusing their attention on the information and procedures they need to learn. Instead, they may be focusing on superficial features,” said Jennifer Kaminski

The problem of distracting visuals is not just an academic issue. In the study, the authors cite real-life examples of colorful, engaging – and possibly confusing – bar graphs in educational materials aimed at children, as well as in the popular media.

And when the authors asked 16 kindergarten and elementary school teachers whether they would use the visually appealing graphs featured in this study, all of them said they would. Intuitively, most of these teachers felt that the graphs with the pictures would be more effective for instruction than the graphs without, according to the researchers.

The findings apply beyond learning graphs and mathematics, the authors said.

“When designing instructional material, we need to consider children’s developing ability to focus their attention and make sure that the material helps them focus on the right things,” Kaminski said.

“Any unnecessary visual information may distract children from the very procedures we want them to learn.”

The main study involved 122 students in kindergarten, first and second grade. All were tested individually.

The experiment began with a training phase where a researcher showed each child a graph on a computer screen and taught him or her how to read it. The children were then tested on three graphs to see if they could accurately interpret them.

The graphs in the training phase involved how many shoes were in a lost and found for each of five weeks. Half the students were presented with graphs in which the bars were a solid color. The other students were shown graphs in which the bars contained pictures of shoes. The number of shoes in the bars was equal to the corresponding y-value on the graph. In other words, if there were five shoes in the lost and found, there were five shoes pictured in the bar.

After the training phase, the children were tested on new graphs in which the bars were either solid-colored or contained pictures of objects such as flowers. However, the number of objects pictured did not equal the correct y-value for the bar. In other words, the bar value could equal 14 flowers, but only seven flowers were pictured.

“This allowed us to clearly identify which students learned the correct way to read a bar graph from those who simply counted the number of objects in each bar,” Sloutsky said.

Sure enough, children who trained with the pictures on the graph were more likely than others to get the answers wrong by simply counting the objects in each bar.

All of the first- and second-graders and 75 percent of the kindergarten children who learned on the solid-bar graphs appropriately read the new graphs.

However, those who learned with the more visually appealing shoe graphs did not do nearly as well. In this case, 90 percent of kindergarteners and 72 percent of first-graders responded by counting the number of flowers pictured. Second-graders did better, but still about 30 percent responded by counting.

All the children were then tested again with graphs that featured patterned bars, with either stripes or polka dots within each bar.

Again, those who learned from the more visually appealing graphs did worse at interpreting these patterned graphs.

“To our surprise, some children tried to count all the tiny polka dots or stripes in the bars. They clearly didn’t learn the correct way to read the graphs,” Kaminski said.

The researchers conducted several other related experiments to confirm the results and make sure there weren’t other explanations for the findings. In one experiment, some children were trained on graphs with pictures of objects. But in this case, the number of objects pictured was not even close to the correct value of the bar, so the students could not use counting as a strategy.

Still, these children did not do as well on subsequent tests as did those who learned on the graphs with single-colored bars.

“When teaching children new math concepts, keeping material simple is very important,” Sloutsky said.

“Any extraneous information we provide, even with the best of intentions, to make the lesson more interesting may actually hurt learning because it may be misinterpreted,” he said.

The researchers said these results don’t mean that textbook authors or others can never use interesting visuals or other techniques to capture the interest of students.

“But they need to study how such material will affect students’ attention. You can’t assume that it is beneficial just because it is colorful; in can affect learning by distracting attention from what is relevant,” Sloutsky said.

Abstract of the research:

Educational material often includes engaging perceptual information. However, this perceptual information is often extraneous and may compete with the deeper to-be-learned structure, consequently hindering either the learning of relevant structure or its transfer to new situations. This hypothesis was tested in 4 experiments in which 6- to 8-year-old children learned to read simple bar graphs. In some conditions, the bars were monochromatic (i.e., No Extraneous Information), whereas in other conditions, the bars consisted of columns of discrete countable objects (i.e., Extraneous Information). Results demonstrated that the presence of extraneous information substantially attenuated learning; participants tended to count the objects and failed to acquire the appropriate strategy. The interference effects decreased with age. These findings present evidence of how extraneous information affects learning of new mathematical knowledge. Broader implications of these findings for understanding the development of the ability to filter task-irrelevant information and for educational practice are also discussed.

I found this research at the University of Hong Kong by David M. Kennedy and Bob Fox through Net Gen Skeptic. There haven’t been that much research on digital skills that left the VS or Europe. The paper concludes that digital natives exist, but with some important nuances.

In Digital natives’: An Asian perspective for using learning technologies, the authors investigated how first year undergraduate students used and understood various digital technologies.  The first-year undergraduate students at HKU do use a wide range of digital technologies.

Students use a raft of technologies for communication, learning, staying connected with their friends and engaging with the world around them. But the students are using them primarily for “personal empowerment and entertainment” and that the students were “not always digitally literate in using technology to support their learning. This is particularly evident when it comes to student use of technology as consumers of content rather than creators of content specifically for academic purposes”

Actually the research doesn’t tell us anything if they are truly digital natives in being much different or better in using technology. It does show that are still important caveats.

Abstract of the research paper that can be downloaded here:

Students entering universities in the 21st century have been described variously as digital natives, the millennial generation or the net generation. Considerable study has occurred around the world to determine the knowledge, skills, understanding and the purposes to which this group of individuals makes technology work for them. A number of researchers have begun to question some of the claims made for this group in terms of their ability to engage with and use technology for learning. To date there has been little information specific to the Asian learner and their use of technology. This paper begins with a description and analysis of a survey that examined the knowledge, skills and understanding of students entering first-year undergraduate studies at the University of Hong Kong. This description is followed by a discussion of the potential impact this has for the design of learning environments in higher education.

Just wait a minute, can you really be allergic to school? Well, kind of. New research published in the May issue of Annals of Allergy, Asthma & Immunology shows that dustless chalk that is being used to keep hands and classrooms clean may cause allergy and asthma symptoms in students that have a milk allergy.

From the press release:

Casein, a milk protein, is often used in low-powder chalk. When milk allergic children inhale chalk particles containing casein, life-threatening asthma attacks and other respiratory issues can occur.

“Chalks that are labeled as being anti-dust or dustless still release small particles into the air,” said Carlos H. Larramendi, MD, lead study author. “Our research has found when the particles are inhaled by children with milk allergy, coughing, wheezing and shortness of breath can occur. Inhalation can also cause nasal congestion, sneezing and a runny nose.”

Milk allergy affects an estimated 300,000 children in the United States, according to the ACAAI. Although it has been believed the majority of children will outgrow milk allergy by age three, recent studies contradict this theory, showing school aged children are still affected. However, 80 percent of children with milk allergy will likely outgrow it by age 16.

“Chalk isn’t the only item in a school setting that can be troublesome to milk allergic students,” said James Sublett, MD, chair of the ACAAI Indoor Environment Committee. “Milk proteins can also be found in glue, paper, ink, and in other children’s lunches.”

Even in the wake of whiteboards, overhead projectors and tablets, chalk is a classroom staple that likely won’t become extinct anytime soon. Parents with milk allergic children should ask to have their child seated in the back of the classroom where they are less likely to inhale chalk dust, advises Sublett.

Abstract of the research:

Background: Nondietary exposure to milk proteins may be a risk for children who do not outgrow milk allergy by school age.

Objective: To study the allergenicity of casein containing chalk.

Methods: A 6-year-old, milk allergic child developed asthma and rhinoconjunctivitis while in school. The suspected cause was dust-free chalk containing casein. To study the relationship of dust-free chalk containing casein with asthma and rhinoconjunctivitis, 13 additional milk allergic patients were studied: 3 school-aged children, 8 preschool-aged infants, and 2 children with outgrown milk allergy. Skin tests and/or specific IgE with chalk and casein were performed. A chalk use test was performed in older children. Milk allergens contained in chalk were characterized by sodium dodecyl sulfate–polyacrylamide gel electrophoresis, immunoblot, and IgE inhibition experiments.

Results: All school-aged, milk allergic children were exposed to chalk and reported symptoms attributed to chalk exposure. The skin test result to chalk was positive in 5 of 12 cases, and the specific IgE test result was positive in all 12 study participants in which it was performed. Casein strongly inhibited the binding of IgE to chalk. Chalk sodium dodecyl sulfate–polyacrylamide gel electrophoresis showed proteins with molecular weight similar to caseins. Immunoblot demonstrated strong binding of IgE to chalk in a blurred pattern and a band at 30 kDa, inhibited by casein. The chalk challenge test result was positive in 2 school-age children who had a positive skin test result to chalk. Their symptoms improved after avoidance of chalk in the school. In 2 other cases in which the challenge test result was negative, chalk was reintroduced without problems.

Conclusion: Inhalation of chalk dust containing casein can induce asthma symptoms in milk allergic patients. Hidden and nondietary sources of exposure should always be considered in food allergic patients.

Classes in Europe are getting more diverse by the year. Does this have an influence on the educational performance in primary education. This was the subject of research by Veerman et al. in the Netherlands.

In their research they make a distinction between the proportion of migrants (first- and second-generation) and the diversity among the different origin groups.

From the conclusion:

Our results demonstrated that the proportion of migrants in a class is negatively related to academic performance of native pupils. Pupils of migrant origins are less strongly affected by larger proportions of migrants in a class. The diversity of pupils in terms of origin has weaker effects overall, although the reading comprehension of children with a migration background is negatively related to origin diversity in Grade 8, the year in which decisions are made for the school type that can be attended in secondary education.
This conforms to the study of Van Ewijk and Sleegers (2010a), who demonstrated that peergroup effects increase as pupils get older.
Also children of Dutch descent had slightly lower scores on reading comprehension if they were in a class with a larger number of different origin groups. So, instructional problems resulting from a larger number of origin groups in a class were more negatively affecting children of Dutch descent. The combined results suggest that for reading comprehension in Grade 8 native pupils are significantly influenced by instructional mechanisms and migrant pupils by a combination of instructional and peer group mechanisms.
The difference between math and reading comprehension for the effect of the number of origin groups for native pupils in Grade 8 could possibly be caused by the different instructional needs of the pupils with respect to math and reading comprehension. For instance, for reading comprehension native pupils possibly need more instruction that connects to their own needs as natives. The results suggest that teachers have more problems with also planning the instruction for the needs of the native pupils. Nevertheless, for math the teachers could possibly instruct more origin groups at the same time.
Our findings of origin diversity residuals in Grade 8 are partially in line with the earlier research of Dronkers and Van der Velden (in press). Using data from diverse OECD countries, Dronkers and Van der Velden found significant negative effects of origin diversity on reading scores for migrants in secondary schools. Nevertheless, in contrast to this earlier study we found in our research model no significant effects for mathematics.

Abstract of the research that can be downloaded here:

This article examines the effect of the ethnic composition in the school class on school performance in primary education, using COOL 2008 data for The Netherlands. We make an important distinction between the proportion of migrant children and the diversity with regard to the different ethnic groups in a school class. Due to the strong correlation between these 2 variables, we employ a residualized score of diversity on the proportion of migrants. The diversity indicator, which indicates the level of diversity given a particular share of migrant children, is negatively related to reading comprehension in Grade 8. For other grade years, we find little support for negative effects of diversity net of the share of migrants in a class.

Some people may think if being an expert in your field makes you a better teacher, and although you need to be sufficient in the know in the topic your teaching, being a bigger expert doesn’t make you a better teacher by definition. As part of an unusual study by Sadler et al. showed that while most of the teachers were well-versed in their subject, those better able to predict their students’ wrong answers on standardized tests helped students learn the most.  Sadler and his colleagues tested 181 middle school physical science teachers and 9556 of their students.

From the press release:

For the study described in their paper, Sadler and his colleagues asked teachers to answer each question twice, once to give the scientifically correct answer, and the second time to predict which wrong answer their students were likeliest to choose. Students were then given the tests three times throughout the year to determine whether their knowledge improved.

The results showed that students’ scores showed the most improvement when teachers were able to predict their students’ wrong answers.

“Nobody has quite used test questions before in this way,” Sadler said. “What I had noticed, even before we did this study, was that the most amazing science teachers actually know what their students’ wrong ideas are. It occurred to us that there might be a way to measure this kind of teacher knowledge easily without needing to spend long periods of time observing teachers in their classrooms.”

To help teachers hone this knowledge, Sadler and his colleagues have made the kind of tests used in their study publicly available. More than a dozen tests covering kindergarten through grade 12 are downloadable here, after completing a tutorial on their development and interpretation.

Going forward, Sadler said he hopes to conduct similar studies in the life sciences, particularly around concepts such as evolution and heredity. He also plans to study what types of professional development and new teacher preparation programs help improve instructors’ facility in knowing what their students know.

Ultimately, Sadler said, he hopes teachers will be able to use the tests to help design lessons that change students’ incorrect ideas and help them learn science more quickly and easily. This is particularly important as states adopt the recently released Next Generation Science Standards.

“State certification for teaching science might well include making sure that new teachers are aware of the common student misconceptions that they will encounter, as well as being proficient in the underlying science,” said Sadler. “Prior to this, there has never been an easy way to measure teachers’ knowledge of student thinking, while we have probably been placing too much emphasis on testing for advanced scientific knowledge.

“Everyone has had a teacher or professor who is incredibly knowledgeable about their field, yet some of them are less-than-stellar teachers,” he continued. “One of the reasons for this is that teachers can be unaware of what is going on in their students’ heads, even though they may have had exactly the same ideas when they were students themselves. Knowledge of student misconceptions is a critical tool for science teachers. It can help teachers to decide which demonstration to do in class, and to start the lesson by asking students to predict what’s going to happen. If a teacher doesn’t have this special kind of knowledge, though, it’s nearly impossible to change students’ ideas.

“The best teachers base their lessons on what the American humorist-philosopher Will Rogers observed: It ain’t what they don’t know that gives them trouble, it’s what they know that ain’t so.”

Abstract of the research:

This study examines the relationship between teacher knowledge and student learning for 9,556 students of 181 middle school physical science teachers. Assessment instruments based on the National Science Education Standards with 20 items in common were administered several times during the school year to both students and their teachers. For items that had a very popular wrong answer, the teachers who could identify this misconception had larger classroom gains, much larger than if the teachers knew only the correct answer. On items on which students did not exhibit misconceptions, teacher subject matter knowledge alone accounted for higher student gains. This finding suggests that a teacher’s ability to identify students’ most common wrong answer on multiple-choice items, a form of pedagogical content knowledge, is an additional measure of science teacher competence.