@article{LevyBrunnerKelleretal.2019,
  author    = {Levy, Jessica and Brunner, Martin and Keller, Ulrich and Fischbach, Antoine},
  title     = {Methodological issues in value-added modeling: an international review from 26 countries},
  series = {Educational Assessment, Evaluation and Accountability},
  volume    = {31},
  journal   = {Educational Assessment, Evaluation and Accountability},
  number    = {3},
  publisher = {Springer},
  address   = {Heidelberg},
  issn      = {1874-8597},
  doi       = {10.1007/s11092-019-09303-w},
  pages     = {257 -- 287},
  year      = {2019},
  abstract  = {Value-added (VA) modeling can be used to quantify teacher and school effectiveness by estimating the effect of pedagogical actions on students' achievement. It is gaining increasing importance in educational evaluation, teacher accountability, and high-stakes decisions. We analyzed 370 empirical studies on VA modeling, focusing on modeling and methodological issues to identify key factors for improvement. The studies stemmed from 26 countries (68\% from the USA). Most studies applied linear regression or multilevel models. Most studies (i.e., 85\%) included prior achievement as a covariate, but only 2\% included noncognitive predictors of achievement (e.g., personality or affective student variables). Fifty-five percent of the studies did not apply statistical adjustments (e.g., shrinkage) to increase precision in effectiveness estimates, and 88\% included no model diagnostics. We conclude that research on VA modeling can be significantly enhanced regarding the inclusion of covariates, model adjustment and diagnostics, and the clarity and transparency of reporting. What is the added value from attending a certain school or being taught by a certain teacher? To answer this question, the value-added (VA) model was developed. In this model, the actual achievement attained by students attending a certain school or being taught by a certain teacher is juxtaposed with the achievement that is expected for students with the same background characteristics (e.g., pretest scores). To this end, the VA model can be used to compute a VA score for each school or teacher, respectively. If actual achievement is better than expected achievement, there is a positive effect (i.e., a positive VA score) of attending a certain school or being taught by a certain teacher. In other words, VA models have been developed to "make fair comparisons of the academic progress of pupils in different settings" (Tymms 1999, p. 27). Their aim is to operationalize teacher or school effectiveness objectively. Specifically, VA models are often used for accountability purposes and high-stakes decisions (e.g., to allocate financial or personal resources to schools or even to decide which teachers should be promoted or discharged). Consequently, VA modeling is a highly political topic, especially in the USA, where many states have implemented VA or VA-based models for teacher evaluation (Amrein-Beardsley and Holloway 2017; Kurtz 2018). However, this use for high-stakes decisions is highly controversial and researchers seem to disagree concerning the question if VA scores should be used for decision-making (Goldhaber 2015). For a more exhaustive discussion of the use of VA models for accountability reasons, see, for example, Scherrer (2011). Given the far-reaching impact of VA scores, it is surprising that there is scarcity of systematic reviews of how VA scores are computed, evaluated, and how this research is reported. To this end, we review 370 empirical studies from 26 countries to rigorously examine several key issues in VA modeling, involving (a) the statistical model (e.g., linear regression, multilevel model) that is used, (b) model diagnostics and reported statistical parameters that are used to evaluate the quality of the VA model, (c) the statistical adjustments that are made to overcome methodological challenges (e.g., measurement error of the outcome variables), and (d) the covariates (e.g., pretest scores, students' sociodemographic background) that are used when estimating expected achievement. All this information is critical for meeting the transparency standards defined by the American Educational Research Association (AERA 2006). Transparency is vital for educational research in general and especially for highly consequential research, such as VA modeling. First, transparency is highly relevant for researchers. The clearer the description of the model, the easier it is to build upon the knowledge of previous research and to safeguard the potential for replicating previous results. Second, because decisions that are based on VA scores affect teachers' lives and schools' futures, not only educational agents but also the general public should be able to comprehend how these scores are calculated to allow for public scrutiny. Specifically, given that VA scores can have devastating consequences on teachers' lives and on the students they teach, transparency is particularly important to evaluate the chosen methodology to compute VA models for a certain purpose. Such evaluations are essential to answer the question to what extent the quality of VA scores allows to base far-reaching decisions on these scores for accountability purposes.},
  language  = {en}
}
@article{LevyMussackBrunneretal.2020,
  author    = {Levy, Jessica and Mussack, Dominic and Brunner, Martin and Keller, Ulrich and Cardoso-Leite, Pedro and Fischbach, Antoine},
  title     = {Contrasting classical and machine learning approaches in the estimation of value-added scores in large-scale educational data},
  series = {Frontiers in psychology},
  volume    = {11},
  journal   = {Frontiers in psychology},
  publisher = {Frontiers Research Foundation},
  address   = {Lausanne},
  issn      = {1664-1078},
  doi       = {10.3389/fpsyg.2020.02190},
  pages     = {18},
  year      = {2020},
  abstract  = {There is no consensus on which statistical model estimates school value-added (VA) most accurately. To date, the two most common statistical models used for the calculation of VA scores are two classical methods: linear regression and multilevel models. These models have the advantage of being relatively transparent and thus understandable for most researchers and practitioners. However, these statistical models are bound to certain assumptions (e.g., linearity) that might limit their prediction accuracy. Machine learning methods, which have yielded spectacular results in numerous fields, may be a valuable alternative to these classical models. Although big data is not new in general, it is relatively new in the realm of social sciences and education. New types of data require new data analytical approaches. Such techniques have already evolved in fields with a long tradition in crunching big data (e.g., gene technology). The objective of the present paper is to competently apply these "imported" techniques to education data, more precisely VA scores, and assess when and how they can extend or replace the classical psychometrics toolbox. The different models include linear and non-linear methods and extend classical models with the most commonly used machine learning methods (i.e., random forest, neural networks, support vector machines, and boosting). We used representative data of 3,026 students in 153 schools who took part in the standardized achievement tests of the Luxembourg School Monitoring Program in grades 1 and 3. Multilevel models outperformed classical linear and polynomial regressions, as well as different machine learning models. However, it could be observed that across all schools, school VA scores from different model types correlated highly. Yet, the percentage of disagreements as compared to multilevel models was not trivial and real-life implications for individual schools may still be dramatic depending on the model type used. Implications of these results and possible ethical concerns regarding the use of machine learning methods for decision-making in education are discussed.},
  language  = {en}
}
@article{KellerKunzeBommeretal.2018,
  author    = {Keller, Sebastian and Kunze, Cindy and Bommer, Martin and Paetz, Christian and Menezes, Riya C. and Svatos, Ales and Dobbek, Holger and Schubert, Torsten},
  title     = {Selective Utilization of Benzimidazolyl-Norcobamides as Cofactors by the Tetrachloroethene Reductive Dehalogenase of Sulfurospirillum multivorans},
  series = {Journal of bacteriology},
  volume    = {200},
  journal   = {Journal of bacteriology},
  number    = {8},
  publisher = {American Society for Microbiology},
  address   = {Washington},
  issn      = {0021-9193},
  doi       = {10.1128/JB.00584-17},
  pages     = {14},
  year      = {2018},
  abstract  = {The organohalide-respiring bacterium Sulfurospirillum multivorans produces a unique cobamide, namely, norpseudo-B-12, which serves as cofactor of the tetrachloroethene (PCE) reductive dehalogenase (PceA). As previously reported, a replacement of the adeninyl moiety, the lower base of the cofactor, by exogenously applied 5,6-dimethylbenzimidazole led to inactive PceA. To explore the general effect of benzimidazoles on the PCE metabolism, the susceptibility of the organism for guided biosynthesis of various singly substituted benzimidazolyl-norcobamides was investigated, and their use as cofactor by PceA was analyzed. Exogenously applied 5-methylbenzimidazole (5-MeBza), 5-hydroxybenzimidazole (5-OHBza), and 5-methoxybenzimidazole (5-OMeBza) were found to be efficiently incorporated as lower bases into norcobamides (NCbas). Structural analysis of the NCbas by nuclear magnetic resonance spectroscopy uncovered a regioselectivity in the utilization of these precursors for NCba biosynthesis. When 5-MeBza was added, a mixture of 5-MeBza-norcobamide and 6-MeBza-norcobamide was formed, and the PceA enzyme activity was affected. In the presence of 5-OHBza, almost exclusively 6-OHBza-norcobamide was produced, while in the presence of 5-OMeBza, predominantly 5-OMeBza-norcobamide was detected. Both NCbas were incorporated into PceA, and no negative effect on the PceA activity was observed. In crystal structures of PceA, both NCbas were bound in the base-off mode with the 6-OHBza and 5-OMeBza lower bases accommodated by the same solvent-exposed hydrophilic pocket that harbors the adenine as the lower base of authentic norpseudo-B-12. In this study, a selective production of different norcobamide isomers containing singly substituted benzimidazoles as lower bases is shown, and unique structural insights into their utilization as co-factors by a cobamide-containing enzyme are provided. IMPORTANCE Guided biosynthesis of norcobamides containing singly substituted benzimidazoles as lower bases by the organohalide-respiring epsilonproteobacterium Sulfurospirillum multivorans is reported. An unprecedented specificity in the formation of norcobamide isomers containing hydroxylated or methoxylated benzimidazoles was observed that implicated a strict regioselectivity of the norcobamide biosynthesis in the organism. In contrast to 5,6-dimethylbenzimidazolyl-norcobamide, the incorporation of singly substituted benzimidazolyl-norcobamides as a cofactor into the tetrachloroethene reductive dehalogenase was not impaired. The enzyme was found to be functional with different isomers and not limited to the use of adeninyl-norcobamide. Structural analysis of the enzyme equipped with either adeninyl-or benzimidazolyl-norcobamide cofactors visualized for the first time structurally different cobamides bound in base-off conformation to the cofactor-binding site of a cobamide-containing enzyme.},
  language  = {en}
}
@article{BrunnerKellerWengeretal.2017,
  author    = {Brunner, Martin and Keller, Ulrich and Wenger, Marina and Fischbach, Antoine and L{\"u}dtke, Oliver},
  title     = {Between-School Variation in Students' Achievement, Motivation, Affect, and Learning Strategies},
  series = {Journal of research on educational effectiveness / Society for Research on Educational Effectiveness (SREE)},
  volume    = {11},
  journal   = {Journal of research on educational effectiveness / Society for Research on Educational Effectiveness (SREE)},
  number    = {3},
  publisher = {Routledge, Taylor \& Francis Group},
  address   = {Abingdon},
  issn      = {1934-5747},
  doi       = {10.1080/19345747.2017.1375584},
  pages     = {452 -- 478},
  year      = {2017},
  abstract  = {To plan group-randomized trials where treatment conditions are assigned to schools, researchers need design parameters that provide information about between-school differences in outcomes as well as the amount of variance that can be explained by covariates at the student (L1) and school (L2) levels. Most previous research has offered these parameters for U.S. samples and for achievement as the outcome. This paper and the online supplementary materials provide design parameters for 81 countries in three broad outcome categories (achievement, affect and motivation, and learning strategies) for domain-general and domain-specific (mathematics, reading, and science) measures. Sociodemographic characteristics were used as covariates. Data from representative samples of 15-year-old students stemmed from five cycles of the Programme for International Student Assessment (PISA; total number of students/schools: 1,905,147/70,098). Between-school differences as well as the amount of variance explained at L1 and L2 varied widely across countries and educational outcomes, demonstrating the limited generalizability of design parameters across these dimensions. The use of the design parameters to plan group-randomized trials is illustrated.},
  language  = {en}
}
@article{KellerCatalaLehnenHuebneretal.2014,
  author    = {Keller, Johannes and Catala-Lehnen, Philip and Huebner, Antje K. and Jeschke, Anke and Heckt, Timo and Lueth, Anja and Krause, Matthias and Koehne, Till and Albers, Joachim and Schulze, Jochen and Schilling, Sarah and Haberland, Michael and Denninger, Hannah and Neven, Mona and Hermans-Borgmeyer, Irm and Streichert, Thomas and Breer, Stefan and Barvencik, Florian and Levkau, Bodo and Rathkolb, Birgit and Wolf, Eckhard and Calzada-Wack, Julia and Neff, Frauke and Gailus-Durner, Valerie and Fuchs, Helmut and de Angelis, Martin Hrabe and Klutmann, Susanne and Tsourdi, Elena and Hofbauer, Lorenz C. and Kleuser, Burkhard and Chun, Jerold and Schinke, Thorsten and Amling, Michael},
  title     = {Calcitonin controls bone formation by inhibiting the release of sphingosine 1-phosphate from osteoclasts},
  series = {Nature Communications},
  volume    = {5},
  journal   = {Nature Communications},
  publisher = {Nature Publ. Group},
  address   = {London},
  issn      = {2041-1723},
  doi       = {10.1038/ncomms6215},
  pages     = {13},
  year      = {2014},
  abstract  = {The hormone calcitonin (CT) is primarily known for its pharmacologic action as an inhibitor of bone resorption, yet CT-deficient mice display increased bone formation. These findings raised the question about the underlying cellular and molecular mechanism of CT action. Here we show that either ubiquitous or osteoclast-specific inactivation of the murine CT receptor (CTR) causes increased bone formation. CT negatively regulates the osteoclast expression of Spns2 gene, which encodes a transporter for the signalling lipid sphingosine 1-phosphate (S1P). CTR-deficient mice show increased S1P levels, and their skeletal phenotype is normalized by deletion of the S1P receptor S1P(3). Finally, pharmacologic treatment with the nonselective S1P receptor agonist FTY720 causes increased bone formation in wild-type, but not in S1P(3)-deficient mice. This study redefines the role of CT in skeletal biology, confirms that S1P acts as an osteoanabolic molecule in vivo and provides evidence for a pharmacologically exploitable crosstalk between osteoclasts and osteoblasts.},
  language  = {en}
}
@misc{BrunnerKellerWengeretal.2017,
  author    = {Brunner, Martin and Keller, Ulrich and Wenger, Marina and Fischbach, Antoine and L{\"u}dtke, Oliver},
  title     = {Between-school variation in students' achievement, motivation, affect, and learning strategies},
  series = {Postprints der Universit{\"a}t Potsdam : Humanwissenschaftliche Reihe},
  journal   = {Postprints der Universit{\"a}t Potsdam : Humanwissenschaftliche Reihe},
  number    = {465},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-412662},
  pages     = {28},
  year      = {2017},
  abstract  = {To plan group-randomized trials where treatment conditions are assigned to schools, researchers need design parameters that provide information about between-school differences in outcomes as well as the amount of variance that can be explained by covariates at the student (L1) and school (L2) levels. Most previous research has offered these parameters for U.S. samples and for achievement as the outcome. This paper and the online supplementary materials provide design parameters for 81 countries in three broad outcome categories (achievement, affect and motivation, and learning strategies) for domain-general and domain-specific (mathematics, reading, and science) measures. Sociodemographic characteristics were used as covariates. Data from representative samples of 15-year-old students stemmed from five cycles of the Programme for International Student Assessment (PISA; total number of students/schools: 1,905,147/70,098). Between-school differences as well as the amount of variance explained at L1 and L2 varied widely across countries and educational outcomes, demonstrating the limited generalizability of design parameters across these dimensions. The use of the design parameters to plan group-randomized trials is illustrated.},
  language  = {en}
}
@article{SchmidtBrunnerKelleretal.2017,
  author    = {Schmidt, Isabelle and Brunner, Martin and Keller, Lena and Scherrer, Vsevolod and Wollschlager, Rachel and Baudson, Tanja Gabriele and Preckel, Franzis},
  title     = {Profile formation of academic self-concept in elementary school students in grades 1 to 4},
  series = {PLoS one},
  volume    = {12},
  journal   = {PLoS one},
  publisher = {PLoS},
  address   = {San Fransisco},
  issn      = {1932-6203},
  doi       = {10.1371/journal.pone.0177854},
  pages     = {27},
  year      = {2017},
  language  = {en}
}
@article{KellerPreckelBrunner2021,
  author    = {Keller, Lena and Preckel, Franzis and Brunner, Martin},
  title     = {Nonlinear relations between achievement and academic self-concepts in elementary and secondary school},
  series = {Journal of educational psychology / American Psychological Association},
  volume    = {113},
  journal   = {Journal of educational psychology / American Psychological Association},
  number    = {3},
  publisher = {American Psychological Association},
  address   = {Washington},
  issn      = {0022-0663},
  doi       = {10.1037/edu0000533},
  pages     = {585 -- 604},
  year      = {2021},
  abstract  = {It is well-documented that academic achievement is associated with students' self-perceptions of their academic abilities, that is, their academic self-concepts. However, low-achieving students may apply self-protective strategies to maintain a favorable academic self-concept when evaluating their academic abilities. Consequently, the relation between achievement and academic self-concept might not be linear across the entire achievement continuum. Capitalizing on representative data from three large-scale assessments (i.e., TIMSS, PIRLS, PISA; N = 470,804), we conducted an integrative data analysis to address nonlinear trends in the relations between achievement and the corresponding self-concepts in mathematics and the verbal domain across 13 countries and 2 age groups (i.e., elementary and secondary school students). Polynomial and interrupted regression analyses showed nonlinear relations in secondary school students, demonstrating that the relations between achievement and the corresponding self-concepts were weaker for lower achieving students than for higher achieving students. Nonlinear effects were also present in younger students, but the pattern of results was rather heterogeneous. We discuss implications for theory as well as for the assessment and interpretation of self-concept.},
  language  = {en}
}
@article{BrunnerKellerStallaschetal.2022,
  author    = {Brunner, Martin and Keller, Lena and Stallasch, Sophie E. and Kretschmann, Julia and Hasl, Andrea and Preckel, Franzis and Luedtke, Oliver and Hedges, Larry},
  title     = {Meta-analyzing individual participant data from studies with complex survey designs},
  series = {Research synthesis methods},
  volume    = {14},
  journal   = {Research synthesis methods},
  number    = {1},
  publisher = {Wiley},
  address   = {Hoboken},
  issn      = {1759-2879},
  doi       = {10.1002/jrsm.1584},
  pages     = {5 -- 35},
  year      = {2022},
  abstract  = {Descriptive analyses of socially important or theoretically interesting phenomena and trends are a vital component of research in the behavioral, social, economic, and health sciences. Such analyses yield reliable results when using representative individual participant data (IPD) from studies with complex survey designs, including educational large-scale assessments (ELSAs) or social, health, and economic survey and panel studies. The meta-analytic integration of these results offers unique and novel research opportunities to provide strong empirical evidence of the consistency and generalizability of important phenomena and trends. Using ELSAs as an example, this tutorial offers methodological guidance on how to use the two-stage approach to IPD meta-analysis to account for the statistical challenges of complex survey designs (e.g., sampling weights, clustered and missing IPD), first, to conduct descriptive analyses (Stage 1), and second, to integrate results with three-level meta-analytic and meta-regression models to take into account dependencies among effect sizes (Stage 2). The two-stage approach is illustrated with IPD on reading achievement from the Programme for International Student Assessment (PISA). We demonstrate how to analyze and integrate standardized mean differences (e.g., gender differences), correlations (e.g., with students' socioeconomic status [SES]), and interactions between individual characteristics at the participant level (e.g., the interaction between gender and SES) across several PISA cycles. All the datafiles and R scripts we used are available online. Because complex social, health, or economic survey and panel studies share many methodological features with ELSAs, the guidance offered in this tutorial is also helpful for synthesizing research evidence from these studies.},
  language  = {en}
}
@article{LehmannKuhnKelleretal.2022,
  author    = {Lehmann, Nico and Kuhn, Yves-Alain and Keller, Martin and Aye, Norman and Herold, Fabian and Draganski, Bogdan and Taube, Wolfgang and Taubert, Marco},
  title     = {Brain activation during active balancing and its behavioral relevance in younger and older adults},
  series = {Frontiers in Aging Neuroscience},
  volume    = {14},
  journal   = {Frontiers in Aging Neuroscience},
  publisher = {Frontiers Media},
  address   = {Lausanne},
  issn      = {1663-4365},
  doi       = {10.3389/fnagi.2022.828474},
  pages     = {20},
  year      = {2022},
  abstract  = {Age-related deterioration of balance control is widely regarded as an important phenomenon influencing quality of life and longevity, such that a more comprehensive understanding of the neural mechanisms underlying this process is warranted. Specifically, previous studies have reported that older adults typically show higher neural activity during balancing as compared to younger counterparts, but the implications of this finding on balance performance remain largely unclear. Using functional near-infrared spectroscopy (fNIRS), differences in the cortical control of balance between healthy younger (n = 27) and older (n = 35) adults were explored. More specifically, the association between cortical functional activity and balance performance across and within age groups was investigated. To this end, we measured hemodynamic responses (i.e., changes in oxygenated and deoxygenated hemoglobin) while participants balanced on an unstable device. As criterion variables for brain-behavior-correlations, we also assessed postural sway while standing on a free-swinging platform and while balancing on wobble boards with different levels of difficulty. We found that older compared to younger participants had higher activity in prefrontal and lower activity in postcentral regions. Subsequent robust regression analyses revealed that lower prefrontal brain activity was related to improved balance performance across age groups, indicating that higher activity of the prefrontal cortex during balancing reflects neural inefficiency. We also present evidence supporting that age serves as a moderator in the relationship between brain activity and balance, i.e., cortical hemodynamics generally appears to be a more important predictor of balance performance in the older than in the younger. Strikingly, we found that age differences in balance performance are mediated by balancing-induced activation of the superior frontal gyrus, thus suggesting that differential activation of this region reflects a mechanism involved in the aging process of the neural control of balance. Our study suggests that differences in functional brain activity between age groups are not a mere by-product of aging, but instead of direct behavioral relevance for balance performance. Potential implications of these findings in terms of early detection of fall-prone individuals and intervention strategies targeting balance and healthy aging are discussed.},
  language  = {en}
}