From Insights to Interventions: Informed Design of Discussion Affordances for Natural Collaborative Exchange

AAAI Conferences

Despite studies showing collaboration to be beneficial both in terms of student satisfaction and learning, isolation is the norm in MOOCs. Two problems limiting the success of collaboration in MOOCs are the lack of support for team formation and structured collaboration support. Lack of support and strategies for team formation prevents teams from being set up for success from the beginning. Lack of structured support during synchronous collaboration has been demonstrated to produce significantly less learning than supported collaboration. This paper describes a deliberation based team formation approach and a scripted collaboration framework for MOOCs aimed at addressing these problems under the umbrella of Discussion Affordances for Natural Collaborative Exchange (DANCE) whose overarching focus is the enhancement of team-based MOOCs. These two examples of current work have been used as illustrations of insights informing interventions in MOOCs.


Comparing Synthesized versus Pre-Recorded Tutor Speech in an Intelligent Tutoring Spoken Dialogue System

AAAI Conferences

We evaluate the impact of tutor voice quality in the context of our intelligent tutoring spoken dialogue system. We first describe two versions of our system which yielded two corpora of human-computer tutoring dialogues: one using a tutor voice prerecorded by a human, and the other using a lowcost text-to-speech tutor voice. We then discuss the results of two-tailed t-tests comparing student learning gains, system usability, and dialogue efficiency across the two corpora and across corpora subsets. Overall, our results suggest that tutor voice quality may have only a minor impact on these metrics in the context of our tutoring system. We find that tutor voice quality does not impact learning gains, but it may impact usability and efficiency for some corpora subsets.


Improving your statistical inferences Coursera

@machinelearnbot

About this course: This course aims to help you to draw better statistical inferences from empirical research. First, we will discuss how to correctly interpret p-values, effect sizes, confidence intervals, Bayes Factors, and likelihood ratios, and how these statistics answer different questions you might be interested in. Then, you will learn how to design experiments where the false positive rate is controlled, and how to decide upon the sample size for your study, for example in order to achieve high statistical power. Subsequently, you will learn how to interpret evidence in the scientific literature given widespread publication bias, for example by learning about p-curve analysis. Finally, we will talk about how to do philosophy of science, theory construction, and cumulative science, including how to perform replication studies, why and how to pre-register your experiment, and how to share your results following Open Science principles.


Improving your statistical inferences Coursera

@machinelearnbot

About this course: This course aims to help you to draw better statistical inferences from empirical research. First, we will discuss how to correctly interpret p-values, effect sizes, confidence intervals, Bayes Factors, and likelihood ratios, and how these statistics answer different questions you might be interested in. Then, you will learn how to design experiments where the false positive rate is controlled, and how to decide upon the sample size for your study, for example in order to achieve high statistical power. Subsequently, you will learn how to interpret evidence in the scientific literature given widespread publication bias, for example by learning about p-curve analysis. Finally, we will talk about how to do philosophy of science, theory construction, and cumulative science, including how to perform replication studies, why and how to pre-register your experiment, and how to share your results following Open Science principles.


Education Secretary Betsy DeVos is getting some very bad news about her favorite thing, school vouchers

Los Angeles Times

A raft of recent studies about school vouchers couldn't have come at a worse time for our new Secretary of Education Betsy DeVos. That's because the studies report devastatingly bad results for students in those voucher programs. And they've been flowing into public forums just as DeVos, a leading advocate of school vouchers, takes charge of federal education policy. DeVos's patron, President Trump, proposed during his campaign to shovel $20 billion to the states to support magnet and charter schools in voucher programs. Voucher programs give parents public funds to spend on approved private schools for their kids.