Chapter 10 Looking Ahead

Question 1

What perception has emerged about higher education in recent years?

Answer 1

It is perceived as an entrenched structure likely to perpetuate inequity.

Question 2

What have many colleges and universities been doing to adapt to contemporary student demands?

Answer 2

Developing programs and services, restructuring organizations, leveraging technology.

Question 3

What significant event intensified the need for transformational change in higher education?

Answer 3

The COVID-19 pandemic.

Question 4

What is a key tool that can help institutions implement necessary reforms?

Answer 4

Data and analytics.

Question 5

What has changed about how students approach higher education?

Answer 5

Students no longer structure their lives around attending college.

Question 6

What do students today value more than prestige and exclusivity?

Answer 6

Personalization, convenience, and flexibility.

Question 7

What should leaders do to create a culture of data integration?

Answer 7

Start small and aim for early visible wins.

Question 8

What is a common challenge faced when integrating data in higher education institutions?

Answer 8

Overcoming internal challenges related to people, processes, data, and technology.

Question 9

What kind of aspiration should institutions create for themselves?

Answer 9

A unique aspiration that includes measurable milestones.

Question 10

When is an ideal time to start building a culture of evidence in a college?

Answer 10

During the arrival of a new president or provost.

Question 11

What is one strategy to ensure effective data usage among various roles in a college?

Answer 11

Create measures that meet the needs of data users.

Question 12

What should any measurement framework be aligned with?

Answer 12

The mission of the institution.

Question 13

True or False: Conversations about data, equity, student success, and financial sustainability should happen separately.

Answer 13

False.

Question 14

What should leaders focus on when starting their analytics journey?

Answer 14

Engaging and incentivizing a coalition of stakeholders willing to use integrated data.

Question 15

What advantages do predictive analytics, learning analytics, artificial intelligence, and machine learning offer to higher education?

Answer 15

They can extract valuable information and yield descriptive analyses.

Question 16

Fill in the blank: Integrated data can reveal opportunities to substantially improve _______.

Answer 16

[return on investment].

Question 17

What does a well-executed data strategy emphasize?

Answer 17

Student success, equity, and organizational sustainability.

Question 18

What can integrated data provide answers to in a campus community?

Answer 18

Key questions about majors, student-faculty ratios, and ideal teaching loads.

Question 19

What is a risk of investing in small programs without a data strategy?

Answer 19

Creating structural budget deficits.

Question 20

What are the key technologies mentioned for enhancing student success?

Answer 20

Predictive analytics, learning analytics, artificial intelligence, machine learning

These technologies can extract valuable information from qualitative data.

Question 21

What is the importance of real-time information in higher education?

Answer 21

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.

Question 22

What challenges do traditional data shops face in higher education?

Answer 22

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.

Question 23

True or False: New approaches to analytics do not carry any risks.

Answer 23

False

New approaches can introduce risks related to privacy, fairness, and biases.

Question 24

What are some recommended steps to prevent bias in analytics?

Answer 24

• 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.

Question 25

What is the role of a data governance group in higher education?

Answer 25

To ensure data quality, anticipate and resolve risks, and scale data use ## Footnote The group addresses embedded biases in data and analyses.

Question 26

What should colleges and universities consider regarding student data?

Answer 26

Engagement with students as equal partners in discussions about data collection and usage ## Footnote This can help build trust and address privacy concerns.

Question 27

What ethical challenges arise from the increasing use of personal data in higher education?

Answer 27

Determining what should and should not be measured, balancing value creation with privacy concerns ## Footnote Leaders must navigate these challenges carefully.

Question 28

What types of data can the Internet of Things devices provide for student performance evaluation?

Answer 28

Data from smartphones, sensors, and other devices can automate evaluations and monitor student activities ## Footnote This raises concerns about privacy and the potential for biased evaluations.

Question 29

What concerns were raised regarding the use of biometric data in higher education?

Answer 29

Privacy violations, potential for biased application, and loss of trust in administration ## Footnote The case at UCLA highlighted these issues.

Question 30

What was the outcome of the MIT case regarding student mental health?

Answer 30

MIT was not held responsible for a student's suicide, highlighting the limits of institutional responsibility ## Footnote The court ruling emphasized the need for attention to mental health issues.

Question 31

What issues arise from integrating external data into higher education systems?

Answer 31

Potential surveillance concerns, privacy issues, and the risk of disadvantaging certain populations ## Footnote Institutions must be cautious about how they use external data.

Question 32

What is the difference between being data-informed and data-driven?

Answer 32

Data-informed institutions use data as a guide, while data-driven institutions may follow data blindly, risking loss of values ## Footnote The distinction is crucial for maintaining the integrity of educational missions.

Question 33

Fill in the blank: Institutions should focus on what __________ should not be measured.

Answer 33

should not be measured ## Footnote This is essential to avoid unnecessary risks and invasiveness.

Question 34

What is a potential risk of normalizing specific actions through automated nudges in higher education?

Answer 34

It may nullify distinctive identities and commitments to equity and upward mobility ## Footnote This highlights the tension between automation and maintaining the unique values of colleges and universities.

Question 35

What might blind faith in the analytics revolution lead colleges and universities to sacrifice?

Answer 35

The individual journey toward learning and self-actualization ## Footnote This emphasizes the importance of personal growth over merely obtaining credentials.

Question 36

Why is it important for college professionals to pay constant attention to data analytics?

Answer 36

To avoid following potentially biased findings at the expense of quality ## Footnote This stresses the need for critical evaluation of data and its implications.

Question 37

What do senior campus leaders need to balance when using data analytics?

Answer 37

Art and science ## Footnote This refers to the need for a nuanced approach in applying data insights to higher education.

Question 38

What is the focus of the current transformation in higher education?

Answer 38

Students rather than on structures or professors ## Footnote This indicates a shift towards student-centered approaches in educational practices.

Question 39

What has the emergence of big data and analytics in higher education been described as?

Answer 39

Having truly transformative potential ## Footnote This suggests that data and analytics could significantly change how education is delivered and experienced.

Question 40

What should college and university leaders aim for when using data and analytics?

Answer 40

To create a more equitable college experience ## Footnote This underlines the goal of leveraging data for social good in education.

Question 41

What can college leaders reinforce by using data well?

Answer 41

The distinctiveness of their institutions ## Footnote This points to the ability of data to help maintain the unique character of educational institutions.

Question 42

What traditions should college leaders honor while innovating through data use?

Answer 42

Shared governance and liberal education ## Footnote This highlights the importance of maintaining traditional educational values amidst modernization.

Question 43

True or False: Higher education has remained stagnant during recent transformative events.

Answer 43

False ## Footnote This indicates that higher education has adapted and evolved in response to recent challenges.

Question 44

Fill in the blank: Colleges and universities must find the right balance for _______.

Answer 44

[themselves] ## Footnote This emphasizes the need for institutions to tailor their approaches to their specific contexts.