Sentences with phrase «data for academic use»

An academic researcher at Cambridge University built an app called thisisyourdigitallife, which offered to pay Facebook users to take a personality test and agree to share that data for academic use.

An academic researcher at Cambridge University built an app called thisisyourdigitallife, which offered to pay Facebook users to take a personality test and agree to share that data for academic use.

Not exact matches

CNBC, which earlier reported the firm's suspension, said people had been misled into believing the quizzes would be used for nonprofit academic research; instead, the data was sold to marketers.

Facebook has said that people who took the quiz were told that their data would be used only for academic purposes, claiming that it and its users were misled by Cambridge Analytica and the researcher it hired, Aleksandr Kogan, a 28 - year - old Russian - American academic.

And while Kogan maintained he had never drawn a salary from the work he did for SCL — saying his reward was «to keep the data», and get to use it for academic research — he confirmed SCL did pay GSR # 230,000 at one point during the project; a portion of which he also said eventually went to pay lawyers he engaged «in the wake» of Facebook becoming aware that data had been passed to SCL / CA by Kogan — when it contacted him to ask him to delete the data (and presumably also to get him to sign the NDA).

Facebook cut off Cubeyou after a CNBC report said that the small data analytics company had misled people into believing its quizzes would be used for nonprofit academic research.

Aleksandr Kogan, a Russian - American academic at Cambridge University, got permission from Facebook to pull data via an app he created — but he reportedly claimed he'd use this data only for academic purposes, not commercial ones.

The Bank has required the securitisation data to be made available to permitted data users (such as those who intend to use the data for investment, professional or academic research).

Facebook has said little about Kogan besides asserting that he lied when he claimed his data - gathering would be used only for academic research.

«The University is concerned, amongst other things, about any issues which may arise from any commercial use» of the personality data and models, which the director said were strictly for academic use.

But Kogan's academic association with Facebook, around the same time that he was taking data to hand off to Cambridge Analytica, raises questions about how user consent was obtained, the line between academic research and corporate marketing — and how scholars can sometimes use data for commercial and political ends.

The sheer volume of data that is now being created presents a significant resource that can be used for the mutual benefit of organisations and academic research.

But Kogan's academic association with Facebook, around the same time that he was taking data to hand off to Cambridge Analytica, raises questions about how user consent was obtained, the line between academic research and corporate marketing — and how scholars can sometimes use data for commercial and political ends.

«The University is concerned, amongst other things, about any issues which may arise from any commercial use» of the personality data and models, which the director said were strictly for academic use.

He said he always assumed the medical data would be anonymous and was intended to be used for an academic project unrelated to his Cambridge Analytica work.

Aleksandr Kogan, a Russian - American academic working with Cambridge Analytica, allegedly violated Facebook's terms of use by saying the data would be used for academic purposes, not political purposes.

He'd presented the app to Facebook and to its users as a project gathering for academic research, but then had turned around and given it to a company that had not been named or identified, and which sought to use the data for political, not academic, purposes.

HGS, he claims, is ready to share data and reagents with them: «We would not block anyone in the academic world from using this for research purposes.»

«We're using climate data that the U.S. federal government supports, so it's freely available and you can go and find it, rather than needing an academic or scientist to look through a microscope and find it for you.»

Vint Cert's highest aspiration for the tool he was creating through the»70s and»80s was that academics might use it to share research data.

Harvard Graduate School of Education will work with the Strategic Education Research Partnership and other partners to complete a program of work designed to a) investigate the predictors of reading comprehension in 4th - 8th grade students, in particular the role of skills at perspective - taking, complex reasoning, and academic language in predicting deep comprehension outcomes, b) track developmental trajectories across the middle grades in perspective - taking, complex reasoning, academic language skill, and deep comprehension, c) develop and evaluate curricular and pedagogical approaches designed to promote deep comprehension in the content areas in 4th - 8th grades, and d) develop and evaluate an intervention program designed for 6th - 8th grade students reading at 3rd - 4th grade level.The HGSE team will take responsibility, in collaboration with colleagues at other institutions, for the following components of the proposed work: Instrument development: Pilot data collection using interviews and candidate assessment items, collaboration with DiscoTest colleagues to develop coding of the pilot data so as to produce well - justified learning sequences for perspective - taking, complex reasoning, academic language skill, and deep comprehension.Curricular development: HGSE investigators Fischer, Selman, Snow, and Uccelli will contribute to the development of a discussion - based curriculum for 4th - 5th graders, and to the expansion of an existing discussion - based curriculum for 6th - 8th graders, with a particular focus on science content (Fischer), social studies content (Selman), and academic language skills (Snow & Uccelli).

There are several possibilities for using administrative data for accountability with respect to academic soft skills.

Students of teachers who hold certification from the National Board for Professional Teaching Standards achieve, on average, no greater academic progress than students of teachers without the special status, a long - awaited study using North Carolina data concludes.

In a new study presented at the this year's fall research conference of the Association for Public Policy Analysis and Management in Chicago, we used data from CORE Districts, to assess whether there are systematic mindset differences present in the US population within and across schools, and whether holding a growth mindset predicts academic achievement gains of students.

COACHE The Collaborative on Academic Careers in Higher Education is a research group that uses data to make the recruitment and management of faculty talent more effective for higher education institutions.

In this webinar, the former chief academic officer for Partnerships to Uplift Communities Schools and now the current chief implementation officer at BloomBoard, Kelly Montes De Oca, will discuss how you can drive more effective professional learning across your school or district by using a framework for instructional improvement focused on data and mastery rather than seat time and credit hours.

Through the Collaborative, Kiernan provides counsel for senior administrators about the academic workplace and the effective use of data for institutional change.

Based on the principles of data - driven instruction, this interactive session will provide an overview of how charter boards can use interim and summative data — academic, financial, and operational — to ensure quality governance that takes into account the Arizona State Board for Charter Schools performance frameworks.

The teacher uses data and collaboration to drive instruction and makes necessary changes to ensure significant academic gains and a powerful learning experience for every child.

Learn best practices for using Perform to enhance instruction, professional learning, and academic achievement through enriched feedback on classroom observations, performance summative evaluations and data analysis.

He credits a number of states, such as Connecticut, Pennsylvania, Minnesota, and Georgia, for using school climate data to engage their school communities «in systemic, relational, or instructional strategies» that support students» academic and social and emotional needs.

Establish procedures to process and place eligible students: develop screening programs in areas of academics and behavior; use data to determine eligibility for special education services; and provide research - based instruction and interventions of increasing intensity of supports to benefit all students

REQUIRED QUALIFICATIONS: A bachelor's degree or higher with at least 24 credit hours in content area Valid IndianaTeaching License for Grades K - 5 or 6 Demonstrates strong writing skills as evidenced by a written response included with Application, answering the following questions: o Describe one experience where you made a significant difference in a student's academic achievement.o Describe a time in which you have used student data to drive greater levels of student achievement.o Describe one way you have successfully integrated technology into your classroom.

For example, spring screening data can be used to provide evidence regarding intervention effectiveness, to evaluate instructional programs, to determine resource allocation (including assignment of students to groups for the following school year), to modify curriculum and instruction, and to monitor overall student growth throughout the academic school yeFor example, spring screening data can be used to provide evidence regarding intervention effectiveness, to evaluate instructional programs, to determine resource allocation (including assignment of students to groups for the following school year), to modify curriculum and instruction, and to monitor overall student growth throughout the academic school yefor the following school year), to modify curriculum and instruction, and to monitor overall student growth throughout the academic school year.

In using ARRA funds, states and school divisions must advance core reforms identified in the legislation, including: implementation of college - and career - ready standards and assessments for all students; establishment of preschool to postsecondary and career longitudinal data systems; improvement in teacher quality — especially for students most at risk of academic failure; and improvement of low - performing schools through effective interventions.

Using Department for Education data on open academies, we looked at every takeover during the 2016 - 17 academic year, as well as schools which are planning to open between now and the end of 2017.

Performance Standard 4: Assessment of and for Student Learning The teacher systematically gathers, analyzes, and uses all relevant data to measure student academic progress, guide instructional content and delivery methods, and provide timely feedback to both students and parents throughout the school year.

It gives parents the tools to evaluate individual programs using academic and demographic data to decide what might be best fit for their child.

A report published by the Collaborative for Academic, Social, and Emotional Learning (CASEL) identifies five key strategies for addressing SEL in ESSA plans, from articulating a well - rounded vision of student success and providing professional development that improves educator SEL capacity to using Title IV grants and making SEL data available to the public.

This report uses the latest data available to look at key transition points for DPS students from 2005 to 2011 to identify: Outcomes and trends in academic achievement and growth as students move from preschool through K — 12 and into college; and Potential barriers to success.

While the field of teacher preparation has made significant advances in recent decades — creating stronger clinical partnerships, developing better performance assessments, making better use of newly available data sources, meeting more demanding state approval and national accreditation standards, and developing new models and patterns of preparation — not all of these advances have been universally adopted at the program level.3 To consolidate the gains and to overcome challenges to implementing universal high standards for admission and academic rigor in teacher preparation, states, school districts, and teacher preparation programs must work together to enact key policy changes.

Any data collected should be used for the sole purpose of tracking the academic progress and needs of students by education officials at the local and state level.

This training module demonstrates how academic progress monitoring fits into the Data - Based Individualization (DBI) process by (a) providing approaches and tools for academic progress monitoring and (b) showing how to use data to using progress monitoring data to set ambitious goals, make instructional decisions, and plan programs for individual students with intensive neData - Based Individualization (DBI) process by (a) providing approaches and tools for academic progress monitoring and (b) showing how to use data to using progress monitoring data to set ambitious goals, make instructional decisions, and plan programs for individual students with intensive nedata to using progress monitoring data to set ambitious goals, make instructional decisions, and plan programs for individual students with intensive nedata to set ambitious goals, make instructional decisions, and plan programs for individual students with intensive needs.

Know how to use data to improve student academic performance using conceptual tools and processes for decision - making.

Performance Management Common Core and Smarter Balanced Assessments; Engaging Math Achievement Strategies; Second Language Learner Considerations in the Common Core; Post-Secondary Readiness; Using Data to Inform Instruction; Acceleration Learning Strategies for Students Below Grade Level; Best Leadership Academic Practices; School Turn - A-Round Best Practices; Coaching; Professional Development; Talent Development; Succession Planning; Principal Evaluations; Teacher Evaluations: Incentive Bonuses and Instructional Leadership.

Are data used to help educators distinguish responsiveness from unresponsiveness for academics?

Using data from National Center for Education Statistics (NCES) restricted - use datasets, the NRCCTE also performs secondary data analyses on questions of vital import to the field of CTE, including exploring the impact of CTE credit - taking on academic outcomes and dropout risk.

For example, the student questionnaire on the National Assessment of Educational Progress, or NAEP, will gather information on students» social - emotional skills in 2017.51 Researchers intend to use these data to analyze the relationship between SEL and academic achievement on the NAEP exam.52 Districts and schools may find this information particularly useful to inform local interventions and improve student performance and behavior.

As Montalvin teachers use inquiry to systematically deepen their understanding of core instructional routines such as math problem solving or academic discussion, their principal has collected data to better understand how to support K / 1 student independence and problem solving in the lunchroom — a pervasive dilemma for elementary school leaders.

A key mechanism for determining the effectiveness of this proficiency - based system is the use of Education Quality Reviews that incorporate quantitative and qualitative data in five dimensions of school quality: academic achievement, personalization, safety and school climate, high - quality staffing, and financial efficiencies.