Chapter 10 Looking Ahead Flashcards
What perception has emerged about higher education in recent years?
It is perceived as an entrenched structure likely to perpetuate inequity.
What have many colleges and universities been doing to adapt to contemporary student demands?
Developing programs and services, restructuring organizations, leveraging technology.
What significant event intensified the need for transformational change in higher education?
The COVID-19 pandemic.
What is a key tool that can help institutions implement necessary reforms?
Data and analytics.
What has changed about how students approach higher education?
Students no longer structure their lives around attending college.
What do students today value more than prestige and exclusivity?
Personalization, convenience, and flexibility.
What should leaders do to create a culture of data integration?
Start small and aim for early visible wins.
What is a common challenge faced when integrating data in higher education institutions?
Overcoming internal challenges related to people, processes, data, and technology.
What kind of aspiration should institutions create for themselves?
A unique aspiration that includes measurable milestones.
When is an ideal time to start building a culture of evidence in a college?
During the arrival of a new president or provost.
What is one strategy to ensure effective data usage among various roles in a college?
Create measures that meet the needs of data users.
What should any measurement framework be aligned with?
The mission of the institution.
True or False: Conversations about data, equity, student success, and financial sustainability should happen separately.
False.
What should leaders focus on when starting their analytics journey?
Engaging and incentivizing a coalition of stakeholders willing to use integrated data.
What advantages do predictive analytics, learning analytics, artificial intelligence, and machine learning offer to higher education?
They can extract valuable information and yield descriptive analyses.
Fill in the blank: Integrated data can reveal opportunities to substantially improve _______.
[return on investment].
What does a well-executed data strategy emphasize?
Student success, equity, and organizational sustainability.
What can integrated data provide answers to in a campus community?
Key questions about majors, student-faculty ratios, and ideal teaching loads.
What is a risk of investing in small programs without a data strategy?
Creating structural budget deficits.
What are the key technologies mentioned for enhancing student success?
Predictive analytics, learning analytics, artificial intelligence, machine learning
These technologies can extract valuable information from qualitative data.
What is the importance of real-time information in higher education?
It meets the demands of college leaders who need timely and fine-tuned analyses to show effective measures over time
Increased volatility in recent decades has raised this demand.
What challenges do traditional data shops face in higher education?
Increased volume of data requests, regimented schedules for compliance reports, discomfort among staff in providing data
They have been molded by historical practices that may not meet current needs.
True or False: New approaches to analytics do not carry any risks.
False
New approaches can introduce risks related to privacy, fairness, and biases.
What are some recommended steps to prevent bias in analytics?
- Be intentional about training data selection
- Question preconceived biases in practices
- Counter dynamic biases in data sets
- Plan data collection and analysis to avoid embedding biases
Recommendations by Chris DeBrusk highlight the need for proactive measures.
What is the role of a data governance group in higher education?
To ensure data quality, anticipate and resolve risks, and scale data use
The group addresses embedded biases in data and analyses.
What should colleges and universities consider regarding student data?
Engagement with students as equal partners in discussions about data collection and usage
This can help build trust and address privacy concerns.
What ethical challenges arise from the increasing use of personal data in higher education?
Determining what should and should not be measured, balancing value creation with privacy concerns
Leaders must navigate these challenges carefully.
What types of data can the Internet of Things devices provide for student performance evaluation?
Data from smartphones, sensors, and other devices can automate evaluations and monitor student activities
This raises concerns about privacy and the potential for biased evaluations.
What concerns were raised regarding the use of biometric data in higher education?
Privacy violations, potential for biased application, and loss of trust in administration
The case at UCLA highlighted these issues.
What was the outcome of the MIT case regarding student mental health?
MIT was not held responsible for a student’s suicide, highlighting the limits of institutional responsibility
The court ruling emphasized the need for attention to mental health issues.
What issues arise from integrating external data into higher education systems?
Potential surveillance concerns, privacy issues, and the risk of disadvantaging certain populations
Institutions must be cautious about how they use external data.
What is the difference between being data-informed and data-driven?
Data-informed institutions use data as a guide, while data-driven institutions may follow data blindly, risking loss of values
The distinction is crucial for maintaining the integrity of educational missions.
Fill in the blank: Institutions should focus on what __________ should not be measured.
should not be measured
This is essential to avoid unnecessary risks and invasiveness.
What is a potential risk of normalizing specific actions through automated nudges in higher education?
It may nullify distinctive identities and commitments to equity and upward mobility
This highlights the tension between automation and maintaining the unique values of colleges and universities.
What might blind faith in the analytics revolution lead colleges and universities to sacrifice?
The individual journey toward learning and self-actualization
This emphasizes the importance of personal growth over merely obtaining credentials.
Why is it important for college professionals to pay constant attention to data analytics?
To avoid following potentially biased findings at the expense of quality
This stresses the need for critical evaluation of data and its implications.
What do senior campus leaders need to balance when using data analytics?
Art and science
This refers to the need for a nuanced approach in applying data insights to higher education.
What is the focus of the current transformation in higher education?
Students rather than on structures or professors
This indicates a shift towards student-centered approaches in educational practices.
What has the emergence of big data and analytics in higher education been described as?
Having truly transformative potential
This suggests that data and analytics could significantly change how education is delivered and experienced.
What should college and university leaders aim for when using data and analytics?
To create a more equitable college experience
This underlines the goal of leveraging data for social good in education.
What can college leaders reinforce by using data well?
The distinctiveness of their institutions
This points to the ability of data to help maintain the unique character of educational institutions.
What traditions should college leaders honor while innovating through data use?
Shared governance and liberal education
This highlights the importance of maintaining traditional educational values amidst modernization.
True or False: Higher education has remained stagnant during recent transformative events.
False
This indicates that higher education has adapted and evolved in response to recent challenges.
Fill in the blank: Colleges and universities must find the right balance for _______.
[themselves]
This emphasizes the need for institutions to tailor their approaches to their specific contexts.
