Category "Life"

Category "Social Science"

Category "Teaching"

May 16, 2006

The Cycle of Life

I just finished teaching Human Development across the Lifespan in Family Contexts. It’s a whirlwind tour of the human lifespan, from conception to death – womb to tomb. It’s a very demanding course because of its sheer breadth. Out of all the possible things I could discuss in the 60 hours I have with the students, and out of all the possible things they could read – what’s most important?

The array of students in the class adds further demands. This term, I had the range from PSEO students (high school students earning college credit) to graduating college seniors – and majors ranging from family social science and child psychology to art, mechanical engineering, and architecture. Where to begin?? How to pitch such a class to satisfy such diverse students’ needs?

One reason I like the course is because it challenges me professionally to think of the interconnectedness of life across the human life course and the role that families and relationships play in development. I’ve also enjoyed the opportunity to learn about topics that have become more salient since I last taught developmental courses – especially about brain development and the biological bases of behavior. (The latter topic takes me back to my graduate student roots in behavioral genetics, which is very exciting.) I have also taken the opportunity to think in “case study? terms about what specific conditions can teach us about human development. This semester, we spent some quality time on 3 “A’s? – autism, ADHD, and Alzheimer’s.

Interesting factoids:
Autism may be due in part to the failure of the brain to prune (selectively destroy) the too-many synapses that are normatively generated during infancy. We are learning a lot about Alzheimer’s from The Nun Study, a research project whose participants are the women from a religious community whose health and psychological histories have been well-documented for many years and who have all agreed to donate their brains to science after they die (since Alzheimer’s cannot be definitively diagnosed except by autopsy.)

As this class ends and I have greeted a number of my students as they walked across the stage in the last commencement ceremony of the College of Human Ecology (1900 – 2006), my own “human development practicum? has awaited me. At one end of the lifespan, my second grandchild ... and first girl (!), Meredith Heller Grotevant, was born Friday, May 12. Her statistics: born at 3:20 pm; 6 lbs, 12 oz.; 19.5 pounds. Mother and baby both came through it with flying colors and father is so proud! (I haven’t heard much about little brother’s reaction yet.) At the other end of the lifespan, my father has needed some new medical interventions that necessitated my travel to his home and retirement community. They don’t call my age group the “sandwich generation? for nothing.

Posted by hgroteva at 9:02 PM | Life | Social Science | Teaching

Category "Social Science"

Category "Teaching"

June 13, 2006

What's Your Number?

I had a conversation with a graduate student last week during which I found myself constructing a scale of expertise in quantitative methods. I've thought about it some more and think it has some interesting ramifications for how we teach methods and statistics, how we train graduate students to be prepared for the job market, and how we select consultants for grants, all of which I do. I'm sharing it here as a work in progress and would be interested in comments and refinements.

In the quantitative spirit, I think of this type of expertise on a quasi-interval scale (more than ordinal but less than interval) from 0 - 5.

A person rated as a 5 on this scale is a methodological and/or statistical innovator. He or she thoroughly understands the math and statistics behind the computer programs and may indeed develop new methods and techniques for solving problems. He or she may also write software to make these techniques available. Here, I'm thinking of a person like Bengt Muthen from UCLA who is a statistician par excellence, develops computer software to make the statistics available and also understands the substantive needs in the field. Or Dave Kenny, who for years has pioneered in developing techniques for analyzing data at the level of the couple and the family.

A person rated as a 4 has strong statistical and methodological skills, but isn't involved in developing new methods or approaches. This person's interests may be more methodological than substantive. (I am not making a value judgment about which is better, since both are essential to progress in the field.) This person may regularly read journals like Psychological Methods or may contribute to special issues of journals that focus on methodology. This is the kind of person who can make strong methodological contributions to a research team as a stats consultant.

A person rated as a 3 has strong understanding of statistics and methods, but is more comfortable with techniques that are tried and true - he/she isn't innovating and isn't choosing to stretch by constantly learning new techniques. However, this person's knowledge is solid and he/she understands key issues and controversies in the field (e.g., data imputation, advantages of latent variable techniques vs. more traditional methods, issues involved in working with couple and/or family-level data, etc.) This person can write syntax for programs such as SPSS, SAS, and STATA and understands what the software does behind the "clicky-boxes." His/her interests are probably more about the substantive issues in the field than about the methodological ones; the methods are a means to an end.

A person rated as a 2 has some understanding of statistics, but generally feels that they are a "black box" - in other words, how they work is mostly a mystery. There is an emerging understanding of how the different statistical methods are related to each other. He/she may be comfortable using drop-down menus to generate analyses in SPSS, for example, but may not be able to generate the syntax that would correspond to the analyses. This person may be quite comfortable with a very limited range of approaches. Once out of his/her comfort zone, this person may feel quite insecure. The substantive issues in his/her field are the primary interest.

A person rated as a 1 on this scale may be able to generate an analysis but probably doesn't understand what the computer software is actually doing and is vulnerable to making mistakes in terms of assumptions, input, and data interpretation. When asked to explain basic statistical concepts, there may be some major points of confusion.

A person rated as a 0 on this scale has a layperson's understanding of statistics and methodology - no specialized training in these fields.

How might this quasi-interval scale apply to the preparation of graduate students? My assumption is that most students entering a masters program in family science have had some undergraduate preparation in methods and statistics, even though they may have learned things by rote and don't remember much. They would probably be at the 1 to 1.5 level. The goal for master's training would be approximately 2.3, where students are definitely comfortable with a range (albeit limited) of techniques. The goal of doctoral training would be to move them as close to a "3" as possible, and possibly beyond. My assumption is that entry level Assistant Professor positions in Research I institutions would be looking for about a 3.5 in terms of expertise. An ideal department would have several faculty comfortably at the 4 level, and a very fortunate department would have someone at the 5 level either in the department itself or psychologically nearby.

So what's your number?

Apart from your self-evaluation, I'd be interested in your thoughts about this scale. I will be teaching the master's level quantitative methods course again next spring and may use this in the class to give students a sense of the range of expertise in the field and help them identify their personal goals for developing quantitative expertise.

Posted by hgroteva at 6:01 PM | Social Science | Teaching