How academics manage individual differences to team teach in higher education: a sociocultural activity theory perspective

Higher Education - In the higher education (HE) landscape worldwide, team teaching has become increasingly common. The growing prevalence of team teaching in HE has mainly been driven by the...     

Challenges and Accomplishments of Practicing Formative Assessment: a Case Study of College Biology Instructors’ Classrooms

International Journal of Science and Mathematics Education - This study presents a glimpse into the private classrooms of biology instructors and the way they practice formative assessments within...     

Relations between informational sources,self-efficacy and academic achievement: a developmental approach

As a cognitive-motivational construct, self-efficacy has been researched extensively and has involved two important lines of inquiries, namely the impact of sources of information on self-efficacy and the predictive effect of self-efficacy on learning outcomes. We proposed and tested the relations between the four major sources of information (enactive performance accomplishments, vicarious experiences, verbal persuasion and emotional and physiological states), self-efficacy and academic achievement for mathematics and science within one conceptual model. Our model was tested with the conjunctive use of longitudinal data and latent growth curve modelling (LGM) procedures. Two hundred and fifty-two (110 girls, 142 boys) upper elementary school children from three government schools participated in this longitudinal study. Likert-scale inventories were administered over four occasions within a one-year period. We measured the four sources of information at T ₁, whereas self-efficacy for mathematics and science was measured at T ₂–T ₄, and academic achievement was measured at T ₄ only. SPSS AMOS v18 was used to test a number of a priori multivariate growth curve models. LGM analyses provided moderate evidence in support of our conceptual model, noting different patterns of trajectories for both mathematics and science.     

Survey reveals slow strides in promoting adolescent reproductive health in Vietnam

This article presents the findings of a survey evaluating the adolescent reproductive health program by the Vietnamese Government. Conducted by the Population Research Consultants, survey findings revealed several setbacks of the adolescent reproductive health program; these included the following: 1) adolescents favor radio, television and newspapers as sources of reproductive health (RH) information; 2) adolescents have no knowledge of pregnancy, sexually transmitted diseases, and HIV/AIDS prevention; 3) the demand for RH information varies according to the sociodemographic characteristics of respondents; 4) while the majority of adolescents do not favor premarital sex and premarital pregnancy, their choice is to keep and deliver the baby in case of a premarital pregnancy; 5) adolescents give a poor rating to the quality of RH/family planning services at the centers; 6) adolescents need to further understand RH but not knowing its meaning, they cannot tell what type of information they require; 6) adolescents have poor knowledge of adolescent reproductive health; 7) friendship and love are often discussed among adolescents, but sexuality rarely is; and 8) adolescents have poor knowledge of RH and poor interest in RH/family planning service facilities.     

A systematic literature review of faculty development for teacher educators

Although ample literature exists regarding the effectiveness of faculty development (FD) activities, there is a gap in the literature synthesizing its outcomes. This review, using a predetermined review protocol, analyzed 22 publications on FD for teacher educators using Kirkpatrick’s training evaluation taxonomy. We found that North American universities provide the most empirical evidence about FD activities, focusing on technology integration in teaching and pedagogical skill improvement. Formal programs, such as serial workshops and developmental relationship, were reported with high frequency, compared to self-directed learning and organizational development activities. Empirical research was heavily based on self-reported, qualitative data and emphasized individual-level outcomes. There is a lack of information regarding the impact of FD activities for teacher educators on subsequent student learning or the downstream effect on school systems. Similarly, institutional involvement in FD remains largely unexplored. We conclude with robust recommendations for research and practice.     

Waiting to decide helps in the face of probabilistic uncertainty but not delay uncertainty

A first-person shooter video game was adapted for the study of causal decision making within dynamic environments. Participants chose which of three potential targets in each of 21 groups was producing distal explosions. The source of the explosion effect varied in the delay between the firing of its weapon and its effect (0.0, 0.5, 1.0, and 2.0 s), the probability that the weapon caused the effect (50%, 75%, and 100%), and the occurrence of auditory events that filled the delay. In Experiment 1, participants’ choice accuracy was highest with short delays but was not affected by probability; participants often compensated for lower probability by increasing their latencies, and thus the number of outcomes sampled. In Experiment 2, a broad range of delays (0–2 s) and probabilities (20%–100%) were randomly sampled for each cause; the results largely replicated those of the prior experiment. The experiments demonstrate people’s ability to successfully modulate their environmental sampling in the face of uncertainty due to lower cause–effect probabilities, but not in the presence of longer cause–effect delays.     

Human and artificial intelligence collaboration for socially shared regulation in learning

Artificial intelligence (AI) has generated a plethora of new opportunities, potential and challenges for understanding and supporting learning. In this paper, we position human and AI collaboration for socially shared regulation (SSRL) in learning. Particularly, this paper reflects on the intersection of human and AI collaboration in SSRL research, which presents an exciting prospect for advancing our understanding and support of learning regulation. Our aim is to operationalize this human-AI collaboration by introducing a novel trigger concept and a hybrid human-AI shared regulation in learning (HASRL) model. Through empirical examples that present AI affordances for SSRL research, we demonstrate how humans and AI can synergistically work together to improve learning regulation. We argue that the integration of human and AI strengths via hybrid intelligence is critical to unlocking a new era in learning sciences research. Our proposed frameworks present an opportunity for empirical evidence and innovative designs that articulate the potential for human-AI collaboration in facilitating effective SSRL in teaching and learning.

Practitioner notes

What is already known about this topic

• For collaborative learning to succeed, socially shared regulation has been acknowledged as a key factor.
• Artificial intelligence (AI) is a powerful and potentially disruptive technology that can reveal new insights to support learning.
• It is questionable whether traditional theories of how people learn are useful in the age of AI.

What this paper adds

• Introduces a trigger concept and a hybrid Human-AI Shared Regulation in Learning (HASRL) model to offer insights into how the human-AI collaboration could occur to operationalize SSRL research.
• Demonstrates the potential use of AI to advance research and practice on socially shared regulation of learning.
• Provides clear suggestions for future human-AI collaboration in learning and teaching aiming at enhancing human learning and regulatory skills.

Implications for practice and/or policy

• Educational technology developers could utilize our proposed framework to better align technological and theoretical aspects for their design of adaptive support that can facilitate students' socially shared regulation of learning.
• Researchers and practitioners could benefit from methodological development incorporating human-AI collaboration for capturing, processing and analysing multimodal data to examine and support learning regulation.