Inclusive education aims to provide learning progress for all. It requires assessments to identify learning levels and progress and to adapt and evaluate instruction. We extend the classroom-based assessment (CBA) approach and argue that CBA in inclusive schools consists of the four dimensions of Instructional Decision-Making, Educational Assessment, Identification of Students with Special Educational Needs, and Progress Monitoring. For this paper, we developed both a framework of CBA for research interests and individual scales for each dimension (6 to 9 items per scale) in order to identify the four dimensions in which teachers need further training. To create a more manageable instrument for education and training practice, we tested a combined model as a questionnaire. In a survey of 110 teachers and 152 pre-service special education teachers (N = 252), the individual scales had good internal consistency (α = .92, .82, .92, .93). Using Confirmatory Factor Analysis, an initial combined model, consisting of the revised individual scales, showed acceptable fit values (CFI = 0.94, TLI = 0.89, RMSEA = 0.07, SRMR = 0.06) almost everywhere. The further development of the questionnaire and its significance and relevance for inclusive educational practice will be discussed.

Reading comprehension at sentence level is a core component in the students' comprehension development, but there is a lack of comprehension assessments at the sentence level, which respect the theory of reading comprehension. In this article, a new web-based sentence-comprehension assessment for German primary school students is developed and evaluated using a curriculum-based measurement (CBM) framework. The test focuses on sentence level reading comprehension as an intermediary between word and text comprehension. The construction builds upon the theory of reading comprehension using CBM-Maze techniques. It is consistent on all tasks and contains different syntactic and semantic structures within the items. This paper presents the test development, a description of the item performance, an analysis of its factor structure, and tests of measurement invariance, and group comparisons (i.e., across gender, immigration background, over two measurement points, and the presence of special educational needs; SEN). Third grade students (n = 761) with and without SEN finished two CBM tests over 3 weeks. Results reveal that items had good technical adequacy, the constructed test is unidimensional, and it is valid for students both with and without SEN. Similarly, it is valid for both sexes, and results are valid across both measurement points. We discuss our method for creating a unidimensional test based on multiple item difficulties and make recommendations for future test construction.

In this study, poor readers in second school year were selected from three schools (n = 32). Their reading skills were surveyed weekly using a CBM instrument over one school semester. Furthermore, they were supported by a five-week reading fluency instruction. The majority of students increased their weekly learning growth in regular teaching and in the phase with the additive instruction. The weekly learning growth was higher in the phase with the additive instruction in reading syllables (b = 0.69), reading words (b = 0.44) and reading comprehension at sentence level (b = 0.45) than without (reading syllables: b = 0.49; reading words: b = 0.18; reading comprehension: b = 0.30). Based on the results of this study, the benefit of CBM for adaptive reading instruction will be discussed.

Our paper introduces and assesses the Levumi platform’s web-based assessment of reading fluency. One challenges of inclusive education is meeting the needs of the learners with special education needs (SEN). Children with SEN and other risk factors face an increased risk of failing in schools and manifesting academic and social problems over the time. Web-based curriculum-based measurement (CBM) can provide an effective tool to track progress of learners and limit such risks. In particular, it can ease the challenges of test administration in inclusive classrooms through automation and providing multiple difficulty levels without the need of different paper-forms. Furthermore, Levumi can help educators track children and thus provide support for learners. Levumi takes advantage of the strengths of web-based CBM to assess reading fluency in primary school students. We confirmed the reading fluency test’s test-retest reliability (n = 334), its ability to measure learning over time in individual learners with SEN (n = 8, across 14 MPs), and its applicability to learners with SEN (n = 300, including n = 46 with SEN). We evaluate Levumi’s overall usefulness in assessing different types of learners, and discuss its contributions to CBM research.

Internationally, teachers use oral reading fluency (ORF) measurements to monitor learning progress in reading and adapt instruction to the individual needs of students. In ORF measures, the child reads aloud single syllables, words, or short passages, and the teacher rates in parallel at which items the child makes a mistake. Since administering paper-based ORF requires increased effort on the part of teachers, computer-based test administration is available. However, there are still concerns about the comparability of paper-based and computer-based test modes. In our study, we examine mode effects between paper-based and computer-based test scores for both reading speed and reading accuracy using a German-language ORF assessment for progress monitoring. 2nd- and 3rd-year-students (N = 359) with and without special education needs participated in the study. Results show comparable and high reliability (r > 0.76) and no differential item functioning for both test modes. Furthermore, students showed significantly higher reading speed on the paper-based test, while no differences were found in reading accuracy. In the absence of differential item functioning, we discuss how mean differences can be accounted for, how teachers can be trained to use the different test modes, and how computer-based tests can be safeguarded in practice.