Desirable skills

This page is the summary section from the complete report.

This section is about desirable skills. The recommendations sections are about desirable tactics for attaining (and fostering) those skills.

Summary

NOTE: when the terms such as “Earth sciences” or “geoscience” are used, they are meant to encompass all geologic, atmospheric, ocean, environment and climate sciences.

Capabilities and attributes that students should be able to demonstrate upon graduation from a quantitatively oriented Earth science (QES) program are described and discussed. This is not about the current QES curriculum in the department of EOAS. That is described on the current QES course content page. Options and preferences are based on input from interviews, surveys and discussions with EOAS faculty and students, from peers and peer institutions, and from literature about career preparation from academic and employer perspectives.

The QuEST project focuses on quantitative earth sciences, and the desirable skills here reflect that. However, the “employability” of a student depends at least as much on abilities and attributes that are not unique to a discipline. Saunders and Zuzel, 2010, quote a useful definition of employability as “a set of achievements – skills, understandings and personal attributes – that make graduates more likely to gain employment and be successful in their chosen occupations, which benefits themselves, the workforce, the community and the economy.” Usher, 2022, discusses some aspects of why it seems difficult for institutions to anticipate market demand – i.e. to define how best to prepare society’s future professionals. Four basic (and perhaps obvious) aspects are (a) the future is hard to predict, (b) companies, governments and universities or colleges do not have the same priorities, (c) companies are precise about skills they want when hiring, but most of those skills arise from experience not academic learning and (d) academics (and institutions) are slow and sometimes reticent to change. Therefore, the majority of desirable skills (with a few exceptions) are considered “generic” rather than targeting specific careers or disciplines.

A slightly more “academic” articulation of forward-looking goals for a university-based undergraduate education is offered by Kwok, 2018 (short, clear, and well worth reading): “A lot of factual information is available on the Internet, and artificial intelligence is making certain occupations obsolete. It is therefore much more important to give our students fundamentals that will stay with them for the rest of their lives. These essential tools include language skills such as comprehension, expression, and communication, as well as quantitative skills such as analysis, seeing hidden patterns, identifying variables, and formulating solutions to problems.” Note that “fundamental skills” here does not refer to “basic theory of a discipline” – it means well-educated, careful, creative and clear ways of thinking.

To reflect the distinction between discipline specific capabilities and the more general characteristics of highly employable graduates, desirable skills identified below are organized into three main categories; (a) knowledge, skills and attitudes that are essentially quantitative (i.e. math, physics and computation), (b) those that are unique to the geosciences, and (c) capabilities associated with a person’s readiness to enter the workforce or advanced education.

Preparing highly employable graduates is not only a responsibility of the Department, but successful graduates are also important from the recruiting or “marketing” perspective.

1.1 Regarding quantitative capabilities

One persistent theme is the importance of “higher-level” aspects of QES learning, i.e. the need to nurture critical thinking involving quantitative and data-oriented information. It takes time and guided practice to gain the necessary maturity to make reliable decisions and judgements based on physics, data sets, and mathematical models.

Quantitative “topics” are easy to list and they seem relatively consistent across QES degree programs. However, rather than listing topics like “ODEs” or “linear algebra”, the important concepts would be more usefully described in terms of the scope, context and expected level of mastery. The department’s research expertise will inform these contexts and those chosen should span the degree specializations, however, students also need to experience settings that reflect the broader world of work.

Computing should be integrated throughout quantitative courses and curriculum. This reflects the growing recognition of computing as a fundamental form of “literacy” across professions (e.g. Guzdial, 2019). A balance is needed between the development of coding skills versus quantitative knowledge that uses computing codes. These two “goals” are not the same and mixing them can compromise success.

AI/ML (including generative AI) is rapidly emerging as a necessary component of thinking across the STEM disciplines. Forward looking curriculum must include opportunities for students to gain mature and well-informed capabilities involving AI.

Sources that consider desirable skills more generally for geoscience graduates are not focused on smaller quantitative programs, but they do remind us that basic numerical capabilities should not be lost in the advanced math; capabilities such as data visualization, managing uncertainty, informed use of statistics, wrangling large and/or public data sets, etc.

Collected quantitative capabilities

To be selected or adjusted and specified with contexts & levels of mastery, appropriately for the specific degree specialization.

  • Pervasive critical quantitative thinking involving numerical, model-based and data-oriented information in Earth science settings.
  • Basic numerical capabilities: fluent algebra & trig, plotting, uncertainty, data organizing, spreadsheet uses.
  • Fundamental math including calculus, ODEs & PDEs, numerical methods – BUT in context.
  • Specialized math including signals and spectra, image analysis, inversion, modelling.
  • Statistics and statistical thinking.
  • Fundamental physics, including mechanics, waves, thermodynamics, continuum mechanics, E&M, measurement, instrumentation.
  • Specialized physics: atmospheric physics, geophysical fluid dynamics, potential fields, waves of all types.
  • Fundamental computing including programming and code-based problem solving, integrated throughout curriculum.
  • Data science, including data access, wrangling, visualization, quality assessment.
  • Pros, cons and ways of applying artificial intelligence and machine learning, including potential and limitations of Generative AI.

1.2 Capabilities unique to the geosciences

Specific geoscience-based capabilities are important because it is the Earth science context that distinguishes an EOAS quantitative degree from a physics, math or computer science degree. Research faculty in quantitative disciplines naturally focus on their own important methods and concepts. But they also tend to gloss over the unique aspects of geoscience and how geoscientists think when hypothesis testing or problem solving. Increasing the attention paid to field, lab, mapping (especially GIS), observational and related skills was considered desirable by employers. Researchers who interact with non-academics also identified these priorities, but purely academic scientists were less likely to mention them. Students also highlight their desire for more “application oriented” settings or contexts while practicing with fundamental concepts.

The distinction between important “geoscience concepts” and important “geoscience skills” was made by the most comprehensive evaluation of current and future geoscience education (Mosher and Keane, 2021). For example, “concepts” include deep time, climate change, Earth materials, natural hazards and others, while “skills” include spatial and temporal interpretation, working with uncertainty, integrating disparate data, and others. This distinction helps clarify how the more quantitative capabilities should be expressed. On their resumes, students need to be able to demonstrate “capabilities” rather than simply listing “concepts encountered”.

One category of capabilities rarely considered in curriculum discussions is the so called “societal relevance skills”. These are important for preventing the sense of “isolated knowledge” that young students experience when learning (for example) basic calculus from abstract mathematical perspectives. When students can articulate the personal and societal relevance of their learning, they are more motivated and consequently more successful.

Collected geoscience capabilities

To be selected or adjusted and specified with contexts & levels of mastery, appropriately for the specific degree specialization.

  • Fundamental geoscience: deep time, rates of geological, atmospheric and ocean processes, scales of influence, spatial information, observational nature of geoscience.
  • Specifics: tectonics, geological materials, resources, hazards, geomorphology, hydrogeology, ocean behavior, basic meteorology and climatology.
  • Field, lab, GIS and observational skills (but not necessarily “specialized” software).
  • Instrumentation, measurement, data management and analysis, where relevant, for geophysical, atmospheric, oceanographic and hydrological work.
  • Multi-disciplinary nature of geoscience (physics, chemistry, biology, geology).
  • Inter-disciplinary nature of the Earth, ocean, atmospheric, and environmental sciences.
  • Societal relevance of geoscience topics, ideally based on engagement with civic or commercial sectors.

1.3 Career-readiness capabilities

Note that interviews were conducted with EOAS faculty to ask specifically about tactics (not skills) they consider effective at helping student prepare for post graduation opportunities. The full report is revealing about different tactics considered important by faculty with different backgrounds and experiences with non-academic sectors. More is discussed in the recommendations section on Career Preparation, and details are in the full report.

Career-readiness capabilities are those aspects of “maturity” sometimes called soft skills, work-place competencies, or something similar. Faculty know these are important and many were mentioned or implied during interviews, including communication skills, teamwork, reliable synthesis of information, and the ability to relate learning to societal and work-place priorities. Conversations focused on tactics for supporting student development rather than articulating the required capabilities. Students certainly benefit from these activities but more clarity about exactly what capabilities are targeted – and why – would increase motivation and help them relate their studies to future occupations.

From the perspective of employers, relevant work experience is highly desirable. This is not a “skill” or “capability” but many employers believe that the “soft skills” and “work-oriented attitudes” can best be obtained in the workplace rather than by studying at school. Unfortunately, finding a first job that is relevant is increasingly difficult. Ng, 2023, refers to this problem as “experience inflation”. Employers also expect students to be able to set appropriate expectations about work habits and the commercial and business aspects of employment. Can degree programs provide relevant experiences without compromising academic priorities? Probably, but a little creativity is needed. Consulting with colleagues, instructional designers and career preparation experts will help weave relevant work-related settings into learning activities. In addition, employers want examples of students applying fundamentals in applied situations, and evidence of a student’s experience in both team-working and leadership roles.

Collected capabilities supporting career & post-graduate readiness

To be selected or adjusted and specified with contexts & levels of mastery, appropriately for the specific degree specialization.

  • Logical and deliberate approaches to problem solving including scientific design and hypothesis testing by observation or experimentation.
  • Develop a sense of curiosity and acquire the confidence to ask questions and challenge assumptions.
  • Synthesis of diverse information & use of public & proprietary literature.
  • Ability to relate learning to societal and work-place priorities.
  • Cooperative aptitudes regarding teams, leadership and self-directed working situations.
  • Communication skills, especially written and oral.
  • Professionalism regarding technical, commercial, business and personal aspects of the workplace.
  • Time or project management tactics practiced (for example) during capstone or project activities.
  • Awareness of the importance of ethics, budgets, balancing needs of clients and employers.
  • Personal skills associated with appropriate behavior regarding justice, equity, diversity and inclusion.
  • Career and self-development skills including life-long learning abilities and habits.
  • Ability to plan for career progress and establish & maintain a network of colleagues and peers to support professional or academic development.
  • Tailor a resume or other expression of personal abilities to suit any relevant job, study or other opportunity.

This page is the summary section from the complete report.