Planning one’s own career is one of the major decisions in life and deciding for a study subject narrows the options for future professions dramatically. While some students have clear career prospects already during high school, others are quite uncertain and rather tend to explore possible pathways. However, Gottfredson (2005) describes that students quickly realize that it is not possible, nor necessary, to explore a broad range of career choices. According to her theory, most occupational aspirations are effortlessly eliminated as unacceptable options while a small set of preferred occupations are carefully weighed but, eventually, all but one will be abandoned. The decision to end the search for alternatives and begin focusing on the establishment of a career is a sign of career maturity according to Super’s (1963) career development theory. Students who do not bring their career exploration to a timely end, particularly during university, are more likely to show a lower commitment to their academic careers and a higher likelihood of dropping out (Perry, Cabrera & Vogt, 1999).

The phenomenon of unsuccessful career exploration is reflected by the substantial number of university students who claim to have false study expectations as a major reason for their decision to end their studies, along with other major reasons such as a lack of study interest and a desire for doing practical work (Heublein et al., 2010; Heublein et al., 2017; Mouton, Zhang & Ertl, 2020). This phenomenon is cited by Klein and Stocké (2016) as indirect evidence of information deficits at the beginning of studies amongst German students. Information deficits have been recognized as a factor that leads to early dropout in the higher education for more than two decades (Schindler, 1997). From a broader European perspective, policy makers have recognized the importance of supporting young adolescents’ career exploration by providing career guidance interventions for students at-risk of dropping out, for example in Ireland and other Scandinavian countries (OECD/European Communities, 2004, p. 18).

However, the findings concerning information deficit’s effects on study outcomes are inconsistent (Klein & Stocké, 2016). Here it should be noted that “information deficit” is used interchangeably with “level of informedness” (Heine et al., 2010; Heublein et al., 2017; Bluthmann, Thiel & Wolfgramm, 2011). Amongst the few studies that investigated informedness, Heublein et al (2010) found no clear differences between the percentage of poorly informed dropouts as compared to graduates who were poorly informed. Conversely, Blüthmann et al. (2011) presented a structural equation model with multiple significant but indirect pathways between informedness and the intention to dropout, such as study conditions, individual study difficulties and interest in their study choice.

To better understand information deficits after the start of university, this study seeks to develop a new operationalization for this construct by grouping students based on their level of informedness and evaluate this operationalization through the career maturity perspective (Super, 1963). This study also aims to find construct validity for informedness groups as an indicator for information deficit. Finally, this study aims to investigate the differences in the level of informedness amongst various study fields and gender.

To address this, our study aims at investigating various theoretically-derived indicators of information deficit and informedness to assist in producing a construct validity for the newly generated informedness groups. This will then be analyzed in through the lens of career maturity. Two research questions will provide context for our analysis of the informedness groups.

Research question 1: How far can the measure of informedness groups be validated by theoretically-derived indicators of information deficit?

Research question 2: Are there differences between genders and study subjects’ areas on their levels of informedness?

The sample of 12143 German university starters from the National Educational Panel Study (NEPS; SC5:14.0.0; see Blossfeld et al., 2011) consisted of 62.4% females, with a mean age of 28.2 years (SD = 4.9 years). Generating Informedness Groups. The Useful Information Sources Questionnaire (USIQ; Heine et al., 2010), administered approximately one year after the start of studies (in wave 2), consists of 15 information sources. Each source was premised with the question “How helpful was the information you received from the people/media/institution listed below for your study decision and planning?” and scored on a scale of 1 (“not helpful at all”) to 4 (“very helpful”), as well as missing response labelled “not used/not offered”. Students are assigned to informedness groups based on their highest ranked usefulness on any USIQ information source, i.e. at least one “very helpful” source means they are including in the Well-Informed group (76.4%), at least one source “rather helpful” in the Fairly-Informed group (22.8%), while all others were assigned to the Poorly-Informed group (.9%). False Study Expectation. The Reason for Dropout Questionnaire (Heublein et al., 2010) is rated on a six-point Likert scale ranging from 1 “plays no role at all” to 6 “plays a very important role”. The focus of this study is on the false study expectation item as a reason for dropout. Intention for Dropout. Intention for Dropout questionnaire is measured by five items (Cronbach’s = .85) from (Trautwein et al., 2007). All items are rated on a four-point Likert scale, ranging from 1 “does not apply at all” to 4 “applies completely”, based on how strongly students have the intention to dropout such as “I have often thought about quitting my studies”. Study Outcome: Failed vs. Successfully finished. Study episodes, containing information where initial studies were either successfully finished or failed, are used to evaluate study outcomes. Several study episodes without a defined status were considered as panel attrition and not included in the analyses. Similarly, a small number of students (<1%) articulated that they abandoned their studies and were therefore not included in the analyses. If more than one study episode started at study entry, a student was considered as successfully finished if any of the episodes were finished successfully. Analysis False Study Expectation and Intention for Dropout are analyzed using one-way analyses of variance, while Study Outcome is reported using a chi square analysis.

This paper began with the aim to investigate the information deficit phenomenon at study entry (Klein & Stocké, 2016) as an indicator for a possible lack of career maturity amongst university starters. This study repurposed the USIQ (Heine et al., 2010) to operationalize information deficits by constructing groups to rank students’ level of informedness. Three distinct yet proportionally lobe-sided groups were constructed. The Well-Informed group represent the majority to the sample. Amongst the two lesser informed groups, more than a fifth of the sample were Fairly Informed, while less than one percent of the students were Poorly Informed. In RQ1, a network of theoretically relevant indicators of information deficits available within NEPS, were used to ascertain whether the informedness groups had predictive construct validity. This study found that students who do not find any source of information they used as optimally useful (i.e. Poorly and Fairly Informed groups) both showed significantly poorer trends on important indicators of information deficit, as compared to their better-informed counterparts (i.e. Well-Informed group). In relation to RQ2, informedness groups presented no significant differences between genders, while the Economics and Engineering study fields were significantly less associated with the Fairly Informed group. This gain in knowledge from the informedness groups could come from two artefacts of the construction method: (1) The differentiation of those who are comprehensively informed and those who are sub-optimally informed; (2) The disaggregation of informedness into a list of types of information sources used, which prompts students to refine their reflection about their level of informedness from various sources as opposed to informedness about different aspects of their studies. The construction of these groups allows for the possibility to further the study of levels of informedness, and by extension information deficits, in relation to applicable models (see Marciniak et al., 2020).

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