This study provides the first large-scale quantitative exploration of mathematical
language use in upper elementary U.S. classrooms employing natural
language processing techniques to describe variation in teachers’ and students’
use of mathematical language in 1,657 fourth and fifth grade lessons in 317
classrooms in four districts over three years.
Students’ exposure to mathematical
language varies substantially across lessons and between teachers. Results suggest
that teacher modeling, defined as the density of mathematical terms in teacher
talk, does not substantially cause students to uptake mathematical language, but
that teachers may encourage student use of mathematical vocabulary by means
other than mere modeling or exposure.
However, the authors also find that teachers who
use more mathematical language are more effective at raising student test scores.
These findings reveal that teachers who use more mathematical vocabulary are
more effective math teachers.
Digital Science, a technology company serving stakeholders across the research ecosystem, is today calling for greater awareness of the impact that a myriad of fast-developing technologies are having on academics and their institutions.
This follows the publication of a new report from Digital Science looking at how changing attitudes and behaviors towards research are affecting traditional research models and dynamics. Key themes to emerge from the findings relate to areas of open research, impact and evaluation, tech and AI, collaboration and research security.
The objective of the report – titled Research Transformation: Change in the era of AI, open and impact – was to learn more about how the research world is experiencing transformation, what’s influencing change and how roles within it are being impacted. Digital Science conducted a survey, reaching out to the research community through questionnaires and in-depth interviews.
Findings from the report may make sobering reading for those involved in academia, as the lightning pace of technological change appears at odds with the traditionally slow-moving nature of the research ecosystem. In total there are five key takeaways:
Open research is transforming research, but barriers remain
Research metrics are evolving to emphasize holistic impact and inclusivity
AI’s transformative potential is huge, but bureaucracy and skill gaps threaten progress
Collaboration is booming, amid increasing concerns over funding and security
Security and risk management need a strategic and cultural overhaul
Digital Science’s new Executive Vice President of Academic, Jonathan Breeze, says: “The Research Transformation: Change in the era of AI, open and impact report gives a voice to the opinions of the academic community and their feelings about changes in the research ecosystem. Importantly, the report gives the whole sector a deeper understanding of the fast-changing needs of academia.
“The report explores how academic roles are evolving, the external drivers of change, and future predictions. It also looks at how Digital Science can support the sector’s changing needs through AI-powered tools and innovations, which is something we’re paying very close attention to across our organization.”
Commenting on the findings, Digital Science’s Mark Hahnel, VP Open Research, and Simon Porter, VP of Research Futures, say: “Our report speaks loudly of the technological advancements, new research practices and global problems driving change in academia. These transformations have created both opportunities and obstacles for institutions and the sector at large.
“Reflecting on the findings, we believe academic institutions can position themselves to deliver meaningful research in the era of three key developments – AI, open research and research impact.”
The report’s findings are based on survey analysis, plus insights from in-depth interviews. The survey was an online questionnaire of open and closed questions that ran during 29 May-12 July 2024 with a total of 380 respondents from 70 countries. Typically, respondents held roles within the academic library, research office, faculty and leadership teams. Further in-depth interviews were held with 15 participants from the academic community over the summer of 2024.
Following the publication of the report, there are also several other activities including a webinar hosted in partnership with Times Higher Education. This webinar will feature a panel discussion on the evolving role of research in academia and the transformative impact of AI and other emerging technologies in making research more open, inclusive, and collaborative.
This study describes the work of the first cohort of 12 grantees of the Statewide Family Engagement Centers program, focusing on the extent to which program priorities were being implemented. Family engagement in education is a long-standing policy priority to promote student success, yet families with low incomes continue to face barriers to involvement in schooling. In 2018, Congress established the Statewide Family Engagement Centers (SFEC) program as a small but key federal investment to help address these disparities. Although the program provides substantial flexibility in how grantees spend their funds, it also requires them to partner with a state education agency, seek wide input on which services to deliver through an advisory committee of families and other representatives, and “serve areas in the state with high concentrations of disadvantaged students.” This report examines how the first set of SFEC grantees carried out their work, including how well aligned they were to program priorities and the factors that affected implementation. Key findings include the following:
Reported implementation four years after the grants began mostly reflected the 2018 federal priorities, including an emphasis on providing direct service to families and schools, some use of other approaches and topics, and expected ways of collaborating with state education agencies.
The districts the SFECs worked with largely had high concentrations of students who were disadvantaged, another priority specified in the law.
In determining how to implement their activities, more SFEC grantees appeared to value direct input from families and education leaders over program requirements or priorities, such as special advisory committees.
Staffing issues, both related and unrelated to the COVID-19 pandemic, were challenges for SFEC implementation.
A new NCES Data Point report, Changes in Public School Teachers’ Certification Type, examines the prevalence of public school teachers who did not hold a teaching certificate or held only provisional or emergency teaching certificates in the state where they were teaching, as opposed to regular, standard, advanced, or probationary certificates. It looks at the prevalence over time, by selected teacher and school characteristics, and by state.
Key findings include the following:
In 2020–21, some 6.9 percent of public school teachers did not hold a teaching certificate or held only provisional or emergency certificates in the state where they were teaching, which was higher than the percentages in 2017–18 (6.2 percent) and in 2015–16 (6.1 percent).
In 2020–21, the percentage was higher for teachers with 3 years or less of teaching experience (25.0 percent), compared to teachers with more experience (ranging from 3.2 percent to 7.2 percent).
The percentage of public school teachers who did not hold a teaching certificate or held only provisional or emergency certificates in the state where they were teaching in 2020–21 varied across states, ranging from 1.9 percent in Iowa to 27.7 percent in the District of Columbia.
This report uses data from the public school teacher files of the National Teacher and Principal Survey (NTPS) for school years 2015–16, 2017–18, and 2020–21.
Policymakers have long debated how to best identify and target resources to the nation’s persistently low-performing schools, which are of particular concern as they often enroll historically underserved students. Most recently, the Every Student Succeeds Act (ESSA) of 2015 sought to address perceived problems with prior federal school accountability policies, including too many schools being labeled as low performing.
This report focuses on state identification of their lowest performing schools, designated as Comprehensive Support and Improvement schools under ESSA. It compares the set of schools identified just before (2016–17) and just after (2018–19) ESSA’s implementation to see if changes to school accountability regulations played out as policymakers expected. Key findings include the following:
Consistent with ESSA’s intent to better focus improvement efforts on the lowest performing schools, a smaller set of schools was identified following ESSA implementation.
At the same time, more alternative, small, and charter schools were identified, which may have resulted from ESSA’s goal to broaden the range of schools eligible for identification.
Finally, while ESSA’s changes did not decrease the identification of schools with the lowest test scores, it may have reduced the focus on schools with high concentrations of historically underserved students.
The author of this reportexamines teacher preferences estimating willingness-to-pay for a rich set of compensation elements and working conditions. Highly effective teachers usually have the same preferences as their peers, but they have stronger preferences for performance pay.
The authoruses the preference estimates to investigate the optimal compensation structure for three key objectives: maximizing teacher utility, maximizing teacher retention, and maximizing student achievement. Under each objective, schools underutilize salary and performance pay, while overutilizing retirement benefits. Restructuring compensation can significantly improve both teacher welfare and student achievement.
The labor-market payoff to workers with associate degrees in healthcare and STEM occupations is very high in Massachusetts. This study examines whether this induced a growing proportion of students in MA community colleges (MACCs) to earn an associate degree (AD) in one of these fields by using multinomial logit analysis to compare trends across 12 cohorts of MACC entrants in the proportion of students who earned an AD in a healthcare or STEM program within six years of entry.
The authors find a substantial increase across cohorts in the proportion of students who earned an AD in a STEM program, but not in the proportion who earned an AD in a healthcare program.They also found differences in degree attainment by student gender, race/ethnicity, family income, and 10th-grade mathematics score. Interviews with MACC program leaders revealed that supply constraints hinder expansion of many healthcare AD programs, but not STEM programs.
