Campus News in Brief
HCI researchers suggest methods to optimize classroom learning
Researchers from Carnegie Mellon University and Temple University recently searched for the best strategies for educating teachers, discovering that finding the best way to teach can be extraordinarily difficult, as there are over 205 trillion potential options available for professors as they form a curriculum.
Ken Koedinger, professor of human-computer interaction at Carnegie Mellon, said “There are not just two ways to teach, as our education debates often seem to indicate.... There are trillions of possible ways to teach.”
According to a university press release, “In the Nov. 22 issue of Science the researchers break down exactly how complicated improving education really is when considering the combination of different dimensions — spacing of practice, studying examples or practicing procedures, to name a few — with variations in ideal dosage and in student needs as they learn.”
The researchers then focused mainly on conclusive approaches that they feel are vital to classroom learning. In order to simplify the complexity of this matter and to help improve educational methods, researchers offered five different suggestions.
Firstly, “Research should focus on how different forms of instruction meet different functional needs,” implementing more experiments “to determine how different instructional techniques enhance different learning functions.”
Researchers also suggested “[taking] advantage of educational technology to further understand how people learn and which instructional dimensions can or cannot be treated independently by conducting massive online studies,” building “a national data infrastructure in which data are collected at a moment-by-moment basis,” and developing “more permanent school and research partnerships to facilitate interaction between education, administration, and researchers.”
Shared information on social networks can lead to hiring discrimination
Alessandro Acquisti, associate professor of information and public policy at Heinz College, and Christina Fong, a senior research student at Dietrich College, headed a research team that found that hiring discrimination can result from employees sharing information on social networks.
Although surveys have suggested that some employers use social networks to screen candidates, until now there have been no controlled experiments that study how often firms look at prospective employees’ online profiles, and how much those profiles affect candidates’ chances.
The researchers found that a minority of American employers consistently refer to online searchers for candidates. According to Fong, “While it appears that a relatively small portion of U.S. employers regularly search for candidates online, we found robust evidence of discrimination among certain types of employers.”
According to a university press release, “Acquisti and Fong used data revealed online by actual members of popular social networking and job-seeking sites to design job candidate résumés and online profiles for their experiments. They experimentally manipulated personal traits the candidates revealed online regarding religion and sexual orientation, while holding signs of professionalism and work ethic constant.” They used more than 1,000 individuals on the Web to test reactions to their profiles and résumés. The two researchers also submitted applications for subjects to over 4,000 employers, which helped them collect data and investigate how many employers looked online for candidates.
The researchers stressed their findings should be seen as correlated — not causal — because they could not randomly assign religious values and traits in different areas. Nonetheless, Acquisti said, “Employers’ use of online social networking sites to research job candidates raises a variety of notable implications, since a vast number of job candidates reveal personal information on these sites that U.S. employers can’t ask in an interview or infer from a résumé.”